🖌️ Sekai (SR003) raised a $23M series A for its AI app creation tool

💻 ZeroDrift (SR006) just announced they’ve raised a $10M seed to enforce compliance on AI communications.

🗽 David Haber says the best founders don’t end up in New York by accident.

💼 Join our talent network for more opportunities. If we see a fit for you, we’ll intro you to relevant founders in the portfolio

Building in public used to be simple. You’d launch on Product Hunt with some story, ask (aka beg) your friends to share it, tweet about it all day, and then hopefully some customers would appear.

The second wave was all about bombast, with indie hackers posting revenue dashboards and selling to the audience watching. But as a general backlash against hustle culture sets in, there are new and better ways of building in public emerging. The new growth meta is to be publicly excellent, making the company itself your content.

Here are three founders who are running this playbook right now.

1) Ship the frontier

As founders, you can live on the edge of the possible with AI models. Whenever a new model drops, it should, hopefully, enable new use cases for your product.

Tom Krcha exemplifies this at Pencil (SR005), the design tool built to live where you code. When Pencil crossed 100,000 users in May, the announcement was about Swarm mode: six AI design agents working a single canvas in parallel. It’s a visually enticing orchestra: a new way of visualizing AI tech at the very cutting edge.

It helps that Krcha is a four-time builder who sold companies to Miro and Google, so these updates read as a frontier operator reporting from the edge rather than a marketer hyping a release.

His video about swarm mode is a perfect example, six agents on one canvas could not have shipped a year ago, which is the line between building in public and posting a changelog.

2) Bet the company in public

If you’ve read any tech-adjacent content you’ll have seen debates on how SaaS companies should adjust their business strategies in the AI era.

One way to build in public is to take a hard stance on this question: pick a business model on the edge of possible, something newly enabled by AI, and tell the story about your ongoing transformation.

Chuck Ganapathi is doing exactly this at Gainsight. In May he told Upstarts that the company, on hundreds of millions in ARR, was going all-in on AI-native services over SaaS, spinning up an agent product called Atlas as its own P&L. A profitable company publicly declared its own core model obsolete! Talk about pivoting in public.

“There would be a revolt if we said we were going to kill that business,” Ganapathi told Upstarts. “But our fundamental belief is that Atlas, and the AI native services business, has a larger market.”

Now there’s a real storyline here worth following: Will Gainsight pull it off? Every update they post from here has added narrative weight because they’ve been so public about the stakes.

3) Hire weird, on purpose

The third version turns who you hire, and on what terms, into the headline. The most legible signal a company sends is the caliber of person willing to join it and the seat they take. When that seat breaks convention, the announcement becomes a build in public moment for staffing.

For example, Jean-Michel Lemieux just ran this at Spellbook, the “Cursor for contracts” startup that raised a $50M Series B from Khosla last October. Lemieux was CTO of Shopify, where he scaled engineering from 50 people to roughly 4,000, and before that ran engineering at Atlassian, helping both companies go from single product to platform. He is a heavy hitter who you would expect to join Spellbook as a CTO. Instead, he joined as something he calls an Executive IC. “It means I’m here to build and be hands on in every part of the company,” he wrote. A person who has held the top engineering seat at two iconic companies took one with no title leverage and no reports, in public, on purpose. This is weird! It’s also cool.It’s a handy way to grab some attention and get a kick ass employee at the same time.

Steak before sizzle

The rule underlying all three of these ideas is that you only earn the right to “build in public” if you’re doing something worth talking about. If you are, your content and your company become the same thing. You have to actually be shipping at the frontier, actually betting the business, actually landing the hire who only makes sense if you’re right. It isn’t about posting grindslop hustleporn about how much you work (spoiler, we are all working hard). It’s about how you’re working differently. The results will speak for themselves.

That’s it for this week! For more weekly dives into the world of early stage startups, subscribe below.

You are receiving this newsletter since you opted in earlier; if you would like to opt out of future newsletters, you can unsubscribe immediately.

This newsletter is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. You should consult your own advisers as to those matters. This newsletter may link to other websites and certain information contained herein has been obtained from third-party sources. While taken from sources believed to be reliable, a16z has not independently verified such information and makes no representations about the enduring accuracy of the information or its appropriateness for a given situation.

References to any companies, securities, or digital assets are for illustrative purposes only and do not constitute an investment recommendation or offer to provide investment advisory services. Any references to companies are for illustrative purposes only; please see a16z.com/investments. Furthermore, this content is not directed at nor intended for use by any investors or prospective investors, and may not under any circumstances be relied upon when making a decision to invest in any fund managed by a16z. (An offering to invest in an a16z fund will be made only by the private placement memorandum, subscription agreement, and other relevant documentation of any such fund which should be read in their entirety.) Past performance is not indicative of future results.

Charts and graphs provided within are for informational purposes solely and should not be relied upon when making any investment decision. Content in this newsletter speaks only as of the date indicated. Any projections, estimates, forecasts, targets, prospects and/or opinions expressed in these materials are subject to change without notice and may differ or be contrary to opinions expressed by others. Please see a16z.com/disclosures for additional important details.

Calling all operators, executives, and the AI-curious! Join us at New York Tech Week for our first ever east coast AI Faire. Meet 20+ speedrun founders and explore live demos of the AI tools they’re building.

One joy of working with founders through speedrun is seeing how quickly teams evolve. Some teams get accepted into the program and end up pivoting completely. They go down a rabbit hole and end up chasing an adjacent idea.

Others stick to their guns and iterate, becoming ever more refined in the process. Concorda (SR006) is one of those. Today, they’re kindly allowing us to show their transformation in public.

Sam Oh and Ke Ma first met in 2021, in an elevator in Chicago in a building where they both lived. Sam was a software engineer at a startup and Ke was attending law school at Northwestern. The two immediately hit it off, and since it was Ke’s birthday, he invited Sam to his party that same day. “We’ve been best friends ever since,” says Ke, now the COO and cofounder of Concorda.

Before founding a startup together, the two did a whirlwind tour of the legal world. Ke worked at McKinsey & Company and as an Assistant State’s Attorney at the Cook County State’s Attorney Office, before leading operations at Sage, a YC-backed startup in the healthcare sector. Sam did tours of duty at Fish & Richardson, Latham & Watkins, and Avantech Law.

The Founder Journey Begins

Sometime in 2025, Sam and Ke got together and began to develop an idea for a startup that would apply agentic AI tech for trial lawyers. The duo found their way to speedrun through a referral to a speedrun investor, Emily Bennett, late in the application cycle for SR006. “We prepared thoroughly for our interviews, pitched our backgrounds, and showed that we had a deep understanding of the market,” Ke says. Emily loved the pitch and extended the team an offer.

From the jump, Concorda had a fairly clear vision and story to tell about what they wanted to build. But that story evolved as they went through speedrun and ultimately pitched at SR006 Demo Day.

To show that evolution, below we’re sharing both the decks Concorda submitted when originally applying to speedrun and when presenting at Demo Day at the conclusion of the 12-week program. (Some numbers redacted for confidentiality.)

Concorda Original Pitch Deck

640KB ∙ PDF file

Download

Download

Concorda Demo Day Pitch Deck

1.19MB ∙ PDF file

Download

Download

Slide 1: Positioning for Ambition

The level-up in the branding is obvious, thanks to the Concorda team leveraging speedrun’s “Brand Lab” program to develop a new logo, color and font system, and style guide. Our own Lester Chen can tell you more about Brand Lab. Onto the content:

The initial pitch of “Agentic AI for Complex Litigation” is defensible and reasonable: exactly what you would expect from former lawyers. But the new version, “AI Operating System for trial lawyers” is more clear about who the end-user is, and the vision is simply bigger. The implication is that ultimately Concorda aims to build everything a trial lawyer needs.

“We learned to be both more precise with our internal plans, and more ambitious in our overall vision for the company,” says Ke.

Slide 2: Dress for Success

One thing that speedrun GP Andrew Chen likes to tell founders is “brag about yourself more.”

If the title slide introduces the vision, the team slide shows why the founders are the best people on the planet to pull this off. Ideally, you establish why you have unfair insights about your target market and why you have the technical chops to build a product that takes advantage of those secrets. “Engineers who try cases. Lawyers who ship code.” is a pithy way to accomplish exactly that.

Slide 3: Show ‘em the Money

Ideas are great, but money talks. When teams apply to speedrun, many don’t have revenue. But by the time you get to Demo Day, it helps to show some progress. Concorda’s real deck had unredacted numbers in straightforward, plain language.

Slide 4: From Mission Statement to Problem Statement

Originally, Concorda’s deck had a slide with a mission statement with callouts annotating which words mean what. But this was a little redundant with the title slide, so Concorda swapped it out for a more compelling problem statement. When presented on stage or on a call with investors, you can extrapolate on a slide like this with anecdotes and specific examples about why it’s a problem that, for example, “generic legal AI has no context.”

In Concorda’s case, they could defend this conclusion by pulling from Sam’s story of being the AI specialist at a litigation boutique and Ke’s background at Cook County State’s Attorney Office. The goal is to show the market the gap you understand better/different than everyone else. Problem statements describe a world the investor already knows is broken. And in this case, it’s a world the founder has already audited firsthand.

Slide 5: TAM and the Limits of the Possible

Let’s be honest: TAM is mostly just a vibe. Nobody actually knows what the TAM for your market is. And besides, generational startups invent markets. They change how work is done.

When making your TAM slide show the key constraints restricting market size, and then show how your product unlocks those constraints. You can be more realistic about it, it makes you more believable.

Slide 6: Send it Home

Concorda took Andrew Chen’s advice to brag more to heart, and ended their Demo Day deck with a humdinger of a brag. Great walk-off line.

That’s it for this week! For more weekly dives into the world of early stage startups, subscribe below.

You are receiving this newsletter since you opted in earlier; if you would like to opt out of future newsletters, you can unsubscribe immediately.

This newsletter is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. You should consult your own advisers as to those matters. This newsletter may link to other websites and certain information contained herein has been obtained from third-party sources. While taken from sources believed to be reliable, a16z has not independently verified such information and makes no representations about the enduring accuracy of the information or its appropriateness for a given situation.

References to any companies, securities, or digital assets are for illustrative purposes only and do not constitute an investment recommendation or offer to provide investment advisory services. Any references to companies are for illustrative purposes only; please see a16z.com/investments. Furthermore, this content is not directed at nor intended for use by any investors or prospective investors, and may not under any circumstances be relied upon when making a decision to invest in any fund managed by a16z. (An offering to invest in an a16z fund will be made only by the private placement memorandum, subscription agreement, and other relevant documentation of any such fund which should be read in their entirety.) Past performance is not indicative of future results.

Charts and graphs provided within are for informational purposes solely and should not be relied upon when making any investment decision. Content in this newsletter speaks only as of the date indicated. Any projections, estimates, forecasts, targets, prospects and/or opinions expressed in these materials are subject to change without notice and may differ or be contrary to opinions expressed by others. Please see a16z.com/disclosures for additional important details.

Next week, Tech Week lands in Boston, followed by NYC. If you’re a founder, check out Pitch Day, a live event at the a16z NY offices where selected founders will have the chance to pitch their company and get feedback from a16z investors.

This is our biggest East coast Tech Week yet, with 2,000+ events happening across both cities. Boston is from May 26 to 31 and NYC is right after from June 1 to 7.

Check out the full calendar and build your own personalized schedule here.

The official application window for SR007 has closed! Investors are now reviewing applications and doing followups to select teams for our Summer/Fall cohort.

If you applied and haven’t heard back, hang tight. We’re reviewing apps on a rolling basis and expect to get back to everyone within ~4 weeks from today.

In the meantime, we know many of you are wondering: what goes on behind the scenes while investors are looking at apps? To answer, we hopped in the booth with Kenan Saleh, Emily Bennett, Fareed Mosavat, and Troy Kirwin from the a16z speedrun investing team to talk about:

00:00 - patterns we’re seeing in apps for SR007
04:50 - our process for reviewing apps
08:20 - traction signals we look for
09:10 - on teams that are a little too early for speedrun
14:26 - surprising things we’ve seen in interviews
20:46 - why you SHOULD NOT take vc funds
25:16 - why should founders pick speedrun?

Watch the full roundtable here:

We’ve put out a lot of content over the last month to explain the speedrun program and what we hope to see from applicants.

Scroll down below to hear directly from 18 different partners from the firm as they explain:

• How the a16z speedrun program supports founders

• The types of startups investors throughout a16z are hoping to invest in

• The big ideas our investors are obsessed with in 2026

If you have questions, shoot us a note at sr-team@a16z.com.

How a16z speedrun Supports Founders

Pitching to VCs is stressful. So we’re turning the tables and pitching to you instead.

The a16z speedrun team has a stacked crew of operators to help you build, scale, and launch your business. Hear from five of our partners below as they explain how they give speedrun founders unfair advantages over the competition.

The Global Founders Program helps you build in America

By Tom Hammer (Head of People, a16z speedrun) - X | LinkedIn

30 of the 70 companies in the last Speedrun batch used our Global Founders Program for help navigating visas and immigration. And not all of those founders were based abroad. For founders on H-1B, TN, or a number of other visas currently working in the US, there’s a path to founding a company and having your own startup sponsor you.

The GTM Team kicks down doors to help you scale

By Macy Mills (Head of GTM, a16z speedrun) - X | LinkedIn

What if I told you I had over 50 executive buyers across Fortune 500 companies, who regularly engage with founders. This year we launched Speedrun Insiders. The exact people you’re trying to get in a room, who will actually take meetings, give feedback, and explore real deployments. We already have them lined up for you, ready to engage.

Brand Lab and Launch Lab make your marketing soar

By Lester Chen (Head of Creators, a16z speedrun) - X | LinkedIn

Every early-stage startup needs attention. Your weekend vibecoded website isn't cutting it. You watch videos but don't know how to make one. 'New media' seems distant, inaccessible. You can't tell your story, so others won't either. Here at speedrun, we’ve designed brand, story, and launch programs to help fix this.

The Talent Network helps you hire

By Bella Nazzari (Talent Partner, a16z speedrun) - X | LinkedIn

We’re the team that helps you hire from the moment you get accepted to speedrun, until well after you finish our program. We’re on track to make over 100 placements across our portfolio this year. Founding engineers, designers, marketers, sales, and all of the new job titles coined this year. No referral fees, no agencies. Direct free hires.

The speedrun marketplace unlocks $7M+ in credits

By Emlyn Thompson (Ecosystem Lead, a16z speedrun) - X | LinkedIn

This is the a16z speedrun Marketplace. Your operating stack, curated and pre-negotiated.We’re talking millions in savings across the tools you actually need: banking, AI, infrastructure, cloud. Everything you need, already onboard.

a16z Team Requests for Startups

The speedrun team partners deeply with the investors on other funds at a16z to find, fund, and support startups. Parters from our Bio + Health, Infrastructure & AI, and American Dynamism teams hopped in the studio to talk about the sort of startups they hope to see.

Early-stage skin cancer detection

By Eva Steinman (Investing Partner, a16z Bio + Health) - X | LinkedIn

Getting to a dermatologist takes three to six months, and in rural areas it often simply doesn't happen at all. We understand how to treat early-stage melanoma. The problem is that we are systematically failing to detect it in time.

A space warfighting prime

By Christian Keil (Investing Partner, American Dynamism) - X | LinkedIn

Combine these ingredients: ubiquitous launch, hundreds of billions of assets in space, and increasingly hostile activity from America’s adversaries… and the opportunity is self-evident. We need the ability to defend our valuable assets on orbit, which is why I want to fund a space warfighting prime.

Video intelligence companies

By Jason Cui (Investing Partner, Infrastructure & AI) - X | LinkedIn

Over the past few years, we've seen remarkable advances in video generation, editing, avatars, and creative tooling. An increasingly important problem is teaching machines to search, analyze, reason over, and extract insight from video across massive libraries and live streams alike.

Infinite healthcare apps

By Jay Rughani (Investing Partner, a16z Bio + Health) - X | LinkedIn

Today, we don't have enough healthcare professionals in America. Wait times to see a doctor average over a month. We're short 600,000+ doctors and nurses. And nearly half of the clinicians we do have are burned out, buried in paperwork. This is a math problem. And AI can fix the equation.

Big Ideas from the Investors

The investors on the speedrun team are always keeping an eye out for the next big bottleneck holding back the future. Below are eight big ideas about what the world needs next from startup founders.

Proactive AI agents

By Kenan Saleh (Investing Partner, a16z speedrun) - X | LinkedIn

Today’s AI products are reactive. You give the model a prompt, it responds with an answer. These are useful, but I’m excited about products that take this further and shift the paradigm from “ask to answer” to “observe to act.”

GUIs for agents

By Jonathan Lai (General Partner, a16z speedrun) - X | LinkedIn

We’re still in the MS-DOS era of agents toda: CLI, terminal sessions, file directories deleted by openclaw etc. while a small slice of silicon valley are power users. At speedrun, we’re looking for bold founders excited to bring the power of agents to normies everywhere.

We’re entering a world of infinite output

By Lejla Johnsen (Investing Partner, a16z speedrun) - X | LinkedIn

What would it look like to create tools that train people to attach real probabilities to their beliefs… and see, over time, where they tend to overestimate or underestimate?Or systems that can make decision-making visible, trackable, and improvable?

Come for the agent, stay for the network

By Troy Kirwin (Investing Partner, a16z speedrun) - X | LinkedIn

In the past, suppliers thrived off of the offline nature of these markets with an agentic platform, the demand side can be aggregated and the power balance flipped. You can start to become the interface buyers default to, the channel suppliers need to be on, and the owner of the richest pricing dataset in the industry.

Tools for the 100x solo founder

By Emily Bennett (Investing Partner, a16z speedrun) - X | LinkedIn

For decades, company size has been dictated by coordination costs. If you wanted to grow revenue, you hired people. More customers meant more support reps. More revenue meant more finance and ops. Scale meant headcount. AI is starting to break that relationship. At speedrun, we’re interested in startups building tools that allow a single founder to operate what would previously have required entire teams.

The next great software distribution company

By Josh Lu (General Manager, a16z speedrun) - X | LinkedIn

For the last decade-plus, building a strong software business was mostly a game of scarcity. The hard part was assembling the capital, taste, engineering, and distribution to build one enduring app. The discovery systems we built matched that world: app stores, SEO, search bars, rankings, reviews, ads, marketplaces. AI has blown up these constraints.

Agent-native products are coming

By Fareed Mosavat (Visiting Partner, a16z speedrun) - X | LinkedIn

Every product on the internet was built for a human with eyes, a cursor, and a credit card. Agents have none of those things. Most companies are teaching agents to pretend to be humans. That's a hack. The real opportunity is products designed for agents from scratch.

New UI/UX paradigms

By Marcus Segal (Investing Partner, a16z speedrun) - X | LinkedIn

The hardest part of software used to be building it, but now it's designing it. Hamburger menus, nav bars, buttons, chat fields... None of these were designed for a world where software participates.

And, lastly, if you’re wondering what actually happens after you hit “submit” on your application:

What happens after you apply to speedrun:

By Ryan Rigney (Marketing Partner, a16z speedrun) - X | LinkedIn

We’re looking for amazing founders. What makes you special, what you understand about this market that other people don't, and evidence that you know how to ship: these are the things that make applications stand out. Traction with customers and an already-assembled killer cofounder team go a long way too.

That’s it for this week! For more weekly dives into the world of early stage startups, subscribe below.

You are receiving this newsletter since you opted in earlier; if you would like to opt out of future newsletters, you can unsubscribe immediately.

This newsletter is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. You should consult your own advisers as to those matters. This newsletter may link to other websites and certain information contained herein has been obtained from third-party sources. While taken from sources believed to be reliable, a16z has not independently verified such information and makes no representations about the enduring accuracy of the information or its appropriateness for a given situation.

References to any companies, securities, or digital assets are for illustrative purposes only and do not constitute an investment recommendation or offer to provide investment advisory services. Any references to companies are for illustrative purposes only; please see a16z.com/investments. Furthermore, this content is not directed at nor intended for use by any investors or prospective investors, and may not under any circumstances be relied upon when making a decision to invest in any fund managed by a16z. (An offering to invest in an a16z fund will be made only by the private placement memorandum, subscription agreement, and other relevant documentation of any such fund which should be read in their entirety.) Past performance is not indicative of future results.

Charts and graphs provided within are for informational purposes solely and should not be relied upon when making any investment decision. Content in this newsletter speaks only as of the date indicated. Any projections, estimates, forecasts, targets, prospects and/or opinions expressed in these materials are subject to change without notice and may differ or be contrary to opinions expressed by others. Please see a16z.com/disclosures for additional important details.

Just fyi that startups applying to speedrun should do it before Sunday, May 17th. If y’all have been waiting for whatever milestone (the demo to be better or metrics or whatever) just apply now. The best founders we fund usually applied too early by their own standards!!

If you’re on the fence, this is the call. Send it in.

More from the team below, plus some of the questions I get asked the most about speedrun.

–A

Andrew Chen
General Partner, a16z speedrun
2865 Sand Hill Rd, Suite 101. Menlo Park CA 94025

__

The questions I get the most

“How do I know if I’m actually cut out to be a founder?”

Honestly, I think most people secretly know if they’re founders or not. Some of you can never be happy working inside a giant company, writing docs, in endless meetings. Deep down, you already know you’re supposed to build. If that describes you, the question isn’t whether you should start a company. It’s just when. There are very few moments in tech I’d rather be a founder in than right now.

“Am I too early to apply? My company isn’t even incorporated.”

That’s actually the sweet spot. In our last batch of 70 companies, probably a dozen were people who hadn’t quit their jobs yet when they applied. They had to turn in their badges, and we couldn’t even wire the money over because they didn’t have a company to incorporate yet. We want to find founders as close to day one as possible. If you’re a couple of friends with a real idea and the willingness to drop everything to go work on it, that’s a speedrun application.

“Do I need a cofounder, or can I apply solo?”

We don’t require it, and we do accept solo founders. But convincing one smart person to join you is probably step one in validating that it’s a serious effort, idea, or team. So we do look at it as a signal. If you have someone in mind but haven’t asked them yet, this is a good week to have that conversation.

“Do I need a specific background to get in?”

There isn’t a checklist. We have a team in the current batch that’s all 18 and 19 year olds who decided to skip college, and we also have cofounders of billion-dollar companies in the same batch. What we look for is something unique in your background. That could be a GitHub repo with thousands of stars growing fast, deep technical work at one of the top AI labs, a serious athletic background on the way to tech, or any number of other things we wouldn’t have predicted. Pedigree is one signal, but it’s not the only one.

“Is speedrun only for AI companies?”

No, it’s a horizontal program. The current batch has B2B, B2C, infra and dev tools, healthcare, gaming, govtech, and a growing number of robotics teams alongside the AI applications. There are also famous examples of ideas changing all the time. Slack started as a browser-based video game company. So if you’re an AI founder today and you end up pivoting in week three, that’s a pretty old Silicon Valley tradition. We care about the founders more than the category.

“I’m outside the US. Can I apply?”

Yes. We select founders from all over the world. This batch has founders applying from the US, India, UK, Nigeria, Canada, and dozens of other countries. If you get in, you and your cofounder will need to come to San Francisco for the 12 weeks of the program, and we help with visa support to make that possible. Don’t let geography stop you from applying.

“Do I have to move to SF?”

For the 12 weeks of the program, yes. You and your cofounder come to San Francisco. We have a welcome guide with recommended neighborhoods, help on Airbnbs, and access to the a16z office and a couple of co-working spaces. Most teams end up rooming with their cofounder for the duration, working together 24/7. After the program ends, plenty of teams go back to their home communities (Austin, Chicago, NYC, Pacific Northwest, wherever they came from, including other countries) and keep building. Plenty stay in the Bay. Both are great outcomes.

“What’s the biggest mistake founders make in the application?”

Being long-winded and vague when you talk about yourselves. A lot of founders bury the lede on their own team. If you started a successful company before, tell us you went from zero to X million in revenue. If you worked on a well-known product, tell us how many millions of users you served. If your side project hit a million downloads, say so. Specific facts and figures help. You can call this bragging. I call it the only good way to pitch a team in writing. (I wrote a longer piece about this called The Dinner Party Jerk Test if you want the full version.)

“What happens if my company doesn’t work out?”

Realistically, a lot of startups don’t. That’s just venture. What we care about is what happens next, and we think of the relationship as a lifelong one, not a batch-long one. The best outcome is we back the founder again on a new idea. We just did that last week with a founder whose first idea didn’t pan out. The other thing we see a lot is speedrun founders hiring each other when one team doesn’t make it, because the people coming through this program are unusually good at working on hard, unstructured problems with the latest AI tools. We want to be in business with these founders for their whole career.

The deadline to apply for SR007 is Sunday, May 17th at 11:59pm PT. Apply here.

You are receiving this newsletter since you opted in earlier; if you would like to opt out of future newsletters, you can unsubscribe immediately.

This newsletter is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. You should consult your own advisers as to those matters. This newsletter may link to other websites and certain information contained herein has been obtained from third-party sources. While taken from sources believed to be reliable, a16z has not independently verified such information and makes no representations about the enduring accuracy of the information or its appropriateness for a given situation.

References to any companies, securities, or digital assets are for illustrative purposes only and do not constitute an investment recommendation or offer to provide investment advisory services. Any references to companies are for illustrative purposes only; please see a16z.com/investments. Furthermore, this content is not directed at nor intended for use by any investors or prospective investors, and may not under any circumstances be relied upon when making a decision to invest in any fund managed by a16z. (An offering to invest in an a16z fund will be made only by the private placement memorandum, subscription agreement, and other relevant documentation of any such fund which should be read in their entirety.) Past performance is not indicative of future results.

Charts and graphs provided within are for informational purposes solely and should not be relied upon when making any investment decision. Content in this newsletter speaks only as of the date indicated. Any projections, estimates, forecasts, targets, prospects and/or opinions expressed in these materials are subject to change without notice and may differ or be contrary to opinions expressed by others. Please see a16z.com/disclosures for additional important details.

⏰ Applications for SR007 close this Sunday, May 17th, at 11:59pm PT! Apply now

🇺🇸 a16z speedrun GP Andrew Chen had a great conversation with Matt Perault about Little Tech on the a16z AI Policy Brief Podcast

🤖 Lejla Johnsen argues that in a world of infinite output, judgment about what to build is what matters

💼 Join our talent network for more opportunities. If we see a fit for you, we’ll intro you to relevant founders in the portfolio

Today’s newsletter is a guest post by a16z speedrun investing partner Emily Bennett. She argues that spotting early markets is a skill: one that founders can learn.

Everybody loves a good market map. It’s seductive to think that you can compress the world into tidy grids with logos neatly sorted into categories, each square representing a company that has raised meaningful capital. For investors, these maps are useful tools to help think through investment opportunities.

They are also, unfortunately, dangerous for founders.

By the time a market is legible enough to be mapped, the most valuable entry points have already closed. The best founders are not waiting for a sector to mature enough that a VC can toss it on a 2x2 it. Generational companies are built by recognizing patterns of behavior that precede the sector map entirely. In my work at a16z speedrun, the most promising opportunities almost never arrive looking like opportunities. They arrive looking strange.

Behavior Comes Before Categories

Markets begin as behavioral shifts in small, overlooked communities. It may be a few hundred developers who can’t stop talking about a new tool. Or maybe there are a few thousand users engaging with an app in ways that seem totally indecipherable to outsiders. The usage numbers are modest, and if you were just glancing at the product, you would probably ignore it.

What matters is the intensity of the behavior. There is a meaningful difference between an app that people open often and an app that changes how people operate. A worldchanging company has to, by its very definition, induce structural new ways of working/being/creating/existing.

Consider OpenClaw. An open-source project built for developers, it required terminal knowledge and real technical fluency. It was not used by everyone. But for those who adopted it, OpenClaw became a fundamental part of their workflow. It reinvented the way they conducted work.

What also made OpenClaw significant was its downstream effects. At speedrun we have already started seeing a new generation of pitches built on the conceptual foundation it propagated. Founders now have proof that agents could be held towards outcomes, not merely tasks completed. Within a week or two of OpenClaws launch, we had pitches for making these systems accessible to non-engineers. Then as the ideas permeated, we started having companies proposing agents that could autonomously run entire business functions, from legal to HR. The agentic workforce thesis now discussed at every conference accelerated across a small developer community restructuring their work around a tool most of the industry had never heard of.

But as a founder, you don’t have to wait for something as popular as OpenClaw to come along.

How to Spot an Early Market

Working with really early-stage companies at speedrun, you start to get a gut sense for whether something is being pulled in by real demand or just pushed out, well before the usual metrics tell you much.

What we try to get founders to look for is simple: are there signs that demand exists even before the product is fully there? The specifics vary, but a few patterns show up a lot.

First is what happens before launch. It is not just about racking up signups. Plenty of subpar products with good marketing campaigns can do that. But is there real intent behind the interest? You can see this in everything that forms around the waitlist. People share it, talk about it, and bring others in without being asked. That energy is coming from the market.

Second is early community. Sometimes people start gathering around a product before it’s even live, and the conversation keeps going on its own. No one from the company is propping it up. People show up because it connects with something they’ve been looking for. Users start creating explainers, tutorials, or threads about the product before there’s any official documentation. They’re doing the company’s marketing without being asked, because they want others to find it.

Third is how intensely a small group uses it once they get access. You’ll see a handful of users spending a surprising amount of time with the product, not because they have to, but because they want to. From there, one of two things usually happens. Either it replaces tools they were already using, or they start bending it into new use cases the founders did not plan for.

Enough of these happen and you know you have something primordial and powerful on your hands.

Building for What You Cannot Yet See

One common failure mode I see from founders is when a team gets stuck building “one more feature” before showing their app to users.

The founders I have seen get this right do something that sounds limiting but is actually the opposite. They pick ten users, maybe fewer, and they go deep. They become almost unreasonably attentive to how those specific people work and what they actually need. And the insights that come out of that kind of closeness are usually generalizable. What ten power users care about tends to map, at least directionally, onto what ten thousand eventual users will care about. Narrowing your focus and shipping live features constantly It is how you earn the right to go broad.

The Map and the Territory

Market maps will keep getting published. They’re useful abstractions, but they’re definitionally lagging. By the time something is legible enough to map, the underlying behavior has already stabilized and the earliest forms of leverage have already been captured.

The next market worth building in is forming right now in a community, or a product, or a pre-order page that no one has yet thought to categorize. Whether you see it depends entirely on whether you are paying attention to behavior or waiting for a label.

For founders, that means building the habit before you need it. You have to haunt the weird corners before they’re legible, the Discord servers with no business model, the subreddits full of complaints about a workflow nobody has named yet. You’re looking for people who have already changed how they hope to work and just haven’t been handed the right product yet.

Thanks to Emily for sharing her insights!

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This newsletter is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. You should consult your own advisers as to those matters. This newsletter may link to other websites and certain information contained herein has been obtained from third-party sources. While taken from sources believed to be reliable, a16z has not independently verified such information and makes no representations about the enduring accuracy of the information or its appropriateness for a given situation.

References to any companies, securities, or digital assets are for illustrative purposes only and do not constitute an investment recommendation or offer to provide investment advisory services. Any references to companies are for illustrative purposes only; please see a16z.com/investments. Furthermore, this content is not directed at nor intended for use by any investors or prospective investors, and may not under any circumstances be relied upon when making a decision to invest in any fund managed by a16z. (An offering to invest in an a16z fund will be made only by the private placement memorandum, subscription agreement, and other relevant documentation of any such fund which should be read in their entirety.) Past performance is not indicative of future results.

Charts and graphs provided within are for informational purposes solely and should not be relied upon when making any investment decision. Content in this newsletter speaks only as of the date indicated. Any projections, estimates, forecasts, targets, prospects and/or opinions expressed in these materials are subject to change without notice and may differ or be contrary to opinions expressed by others. Please see a16z.com/disclosures for additional important details.

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Should you hire two engineers or give one engineer unlimited tokens and nicotine?

The answer to this question is an existential one for startups to answer. Most seed stage startups only have 12-18 months to live. So deciding whether to spend $300,000 a year on agents or using that cash to hire a second engineer is a do or die decision.

So what is a founder to do? Should you be token-maxxing?

The case for going long on tokens

The structural arguments for token-maxxing are that tokens scale linearly with throughput. You can 10x your fleet on a Tuesday afternoon. You cannot 10x your headcount in a day. Additionally, tokens are pure variable cost, with no equity dilution, no demands for green juice and complimentary massages, and no managing someone through a PIP. If the models get better in six months (as they have been) your engineering pipeline gets better.

It is also significantly faster. Founders are building more product in 12 weeks than they used to build in a year. Non-technical founders are shipping enterprise-ready platforms in just a couple of months. The upper bound of what a small team can do has moved, and it has moved fast.

Andrey Starenky at Sentra (SR006) puts a number on it. His team uses Claude Code, Cursor, and OpenCode in whatever combination each engineer prefers, with cloud agents wired into Slack to triage bugs and ship small features the moment a complaint comes in. He pegs the productivity boost at a minimum of 5-10x. The annualized Cursor bill alone, he told us, “is more than the salary of an average engineer.”

The aggressive use cases are even more lopsided. Freddie Wollen from Coalition Systems (SR006) runs agents overnight, attacking his own architecture in search of security flaws. “One workload where spraying tokens at the problem seems like the right answer,” he calls it. The Rust compiler and a strong test suite give the agents a closed feedback loop, so they iterate without supervision while the team sleeps. No human team would do this work, at this scale, for any price.

The point is that the upper bound of what a small team can do has moved, and it has moved fast.

The case for going long on people

Now the other side, just as hard.

When token-maxxing, it can be exceptionally hard to understand what caused the AI to go haywire, and to fix it going forward. With people you can just say “stop doing that or you are fired.”

Simo Rachidi of Safeworld (SR006) builds robotics, where weirdly stupid bugs have physical consequences. He has postponed hiring around internal tools, QA automation, and lightweight full-stack work, but draws a hard line on the roles that carry accountability with tasks like robotics safety, systems architecture, simulation fidelity, and customer trust. “AI gives every engineer more hands,” he says. “It does not replace ownership.”

Token costs are also a moving target, and they have moved in both directions. Frontier model pricing has been reset multiple times in the last two years. A $300K-a-year agent budget in Q1 can become a $500K budget by Q3 if the wrong tier gets repriced. Hiring a person commits you to a salary you can model. Hiring a fleet commits you to a vendor’s roadmap.

The complication

It may be that this is a false binary.

It’s possible founders are not actually foregoing hires because of tokens. Token spend is up. Headcount is also up. Founders are doing both at the same time, or doing neither for unrelated reasons like the funding environment or the difficulty of recruiting in 2026.

Jackie Lunger from Panorama (SR006) told us that her team’s first instinct when agentic tools arrived was to spin up hundreds of agents and let them cook. They coded fast and made the wrong choices. “Coding is actually the easy part,” she says. “The hard part has always been knowing why you are doing what you’re doing.” Now the team invests heavily in planning, and a single agent with clear instructions can one-shot the work. “Spending more tokens usually just means the clarity of thought wasn’t there when the task was started,” Jackie says. “More tokens signal less precision.”

Simo from Safeworld arrives at the same place from a different direction. “I would not call us token-maxxers,” he says. “I would call us failure-mode-maxxers. We use AI aggressively, but the thing we are really maximizing is confidence before deployment.”

If that hypothesis holds, then “token maxing versus hiring” is a false binary, and the real question is something more specific. Which categories of work should be automated, and which categories require a person who can be looked in the eye?

We can all stop asking “tokens or people” and start asking “what kind of work am I actually trying to get done.”

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This newsletter is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. You should consult your own advisers as to those matters. This newsletter may link to other websites and certain information contained herein has been obtained from third-party sources. While taken from sources believed to be reliable, a16z has not independently verified such information and makes no representations about the enduring accuracy of the information or its appropriateness for a given situation.

References to any companies, securities, or digital assets are for illustrative purposes only and do not constitute an investment recommendation or offer to provide investment advisory services. Any references to companies are for illustrative purposes only; please see a16z.com/investments. Furthermore, this content is not directed at nor intended for use by any investors or prospective investors, and may not under any circumstances be relied upon when making a decision to invest in any fund managed by a16z. (An offering to invest in an a16z fund will be made only by the private placement memorandum, subscription agreement, and other relevant documentation of any such fund which should be read in their entirety.) Past performance is not indicative of future results.

Charts and graphs provided within are for informational purposes solely and should not be relied upon when making any investment decision. Content in this newsletter speaks only as of the date indicated. Any projections, estimates, forecasts, targets, prospects and/or opinions expressed in these materials are subject to change without notice and may differ or be contrary to opinions expressed by others. Please see a16z.com/disclosures for additional important details.

Each Tuesday we’ll show up in your inbox with content created to be useful to startup founders and investors. Sometimes it’s a guide or strategy memo from an investor on our team. Other times we go straight to founders or successful creatives to get their advice.

Some recent popular posts:

• Emily Bennett on building financial models

• Troy Kirwin on how to write an investment memo

• Marcus Segal on building processes to find and keep product-market fit

Welcome! And drop us a line by replying to this email if you have any questions that you’d like us to address with future posts.

–The a16z speedrun team

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Today’s essay is a guest post by return contributor Evan Armstrong. Evan is the founder and CEO of The Leverage, a newsletter about how power actually moves in tech.

Evan argues that startups winning in attention marketplaces are investing more in their written product communication, and breaks down the strategies the best founders are using.

For one brief, deliriously delicious moment in the 2010s, cupcakes were the center of the dessert universe. Sprinkles installed 24-hour cupcake ATMs in six cities, each one playing a jingle while a mechanical arm delivered a $4.50 treat. Crumbs Bake Shop went public on NASDAQ, with the stock peaking at $13 a share. The world craved one thing above all else: baked circles topped with 6 tons of powdered sugar.

Then, suddenly, poof.

Crumbs’ stock fell from $13 to four cents. All 65 stores shuttered overnight. Sprinkles, the company that invented the cupcake vending machine, closed permanently on New Year’s Eve 2025. By making cupcakes ubiquitous, the industry had gorged the public on the product until everyone’s taste refined past what most shops could deliver. Only the best cupcake shops have survived.

This is now happening to writing in tech.

AI has made prose cheap. Every seed-stage founder with a pulse and ChatGPT account can produce a competent product update in 90 seconds. Just give an agent access to your codebase, prompt it with “write an email summarizing recent updates we’ve made and the value they’ll offer users” and away you go. This should be the employment apocalypse for the fools who love to wrestle with the written word (aka people like me).

And yet the companies winning in attention marketplaces are investing more in their written product communication, not less. Why? Because when the floor drops to zero, when the world is filled with shitty cupcakes, the ceiling is the only thing that matters.

What a bad feature update looks like

You already know this post. You have written this post:

“We’re excited to announce [Feature]. Here’s what it does. [Screenshot or a GIF if you are feeling fancy.] We can’t wait for you to try it!”

If you stripped away the logo and brand colors, it would be impossible to tell which company in your market wrote that update. If you can swap your name for a competitor’s and the post still reads fine, you have written the cupcake equivalent of a grocery store dessert. It’s fine. Serviceable even. It’s just that nobody will care about it. All of those expensive tokens, all that overpriced engineering time will be greeted with a collective shrug as your customers move on to more interesting things.

Here are three things that you can do to immediately improve your startup’s public facing writing.

1. The why matters over everything

Your customers do not care about your features. I need you to really sit with that and feel it in your bones. They. Do. Not. Care. Most people today have dozens of software products all of which are releasing updates on a near-weekly cadence. The drumbeat of “new feature!” notifications have become white noise, a hum they have long since tuned out. To get them to pay attention, you have to connect it to why you built it.

For an example of this, see how Linear launched Linear Agent this past March. They open the post with a thesis: as execution accelerates, the bottleneck in product development shifts toward judgment about what to build and where your time and tokens are best spent. The product (an AI agent) was the consequence of that strategic claim.

You can easily imagine the version ChatGPT would spit out: “We’re excited to announce Linear Agent: it is not just a new agent, it’s a new way to delve into work.”

In defense of that phrasing, it is accurate! It’s also boring. There is no strategy, no stakes. Customers are betting on startup’s products to wrench them into the future. If you just list out what you released there is no forward momentum to it.

The key test is that if your product update could have been written by anyone with access to your feature spec and a chatbot. The update should contain insights or secrets that only you know—whether that was a customer conversation that sparked the feature build, or your vision for the future.

2. Have an Opinion

When 37signals launched HEY, it would’ve been easy to announce “a new email client with filtering capabilities.” Jason Fried went with the more challenging approach of opening with an argument about the broken state of email: “You started getting stuff you didn’t want from people you didn’t know. You lost control over who could reach you. An avalanche of automated emails cluttered everything up. And Gmail, Outlook, Yahoo, and Apple just let it happen.”

Good products are built off of spiky opinions. Why should good product announcements be any different? The feature was called The Screener, which forced every first-time sender into a purgatory where the user was empowered to decide whether to ever hear from them again. DHH later said The Screener was “a pretty controversial feature to mandate internally” but it became “perhaps the highest profile feature since launch.”

You can disagree with HEY’s take on email! I certainly do. But you cannot confuse it for someone else’s product announcement. Most product updates hedge everything. You can feel the softening of the language, the committee of product managers, marketers, and sales staff that qualified every sentence. Great writing is expensive because it has a point of view the author is willing to defend. Cheap writing reads like it was reviewed by four people who each added a caveat.

You’ll note there isn’t anything about AI tells in this section. LLMs shine in helping you discover what your opinion is, even if the writing they actually suggest is usually mediocre. The only caveat is that they make it incredibly easy to convince yourself into any position. Use AI tools to make sure your argument and opinion are clear. Beware the temptation to use it as a source of validation.

3. Show What You Chose Not to Build

This is my personal favorite, and a perpetually underused tool in the writing tool kit. Write about what you didn’t launch! By walking your users through the very hard trade-offs every product represents, you create a story. Customers view your product as something built with real risks and choices. It draws them in.

When Superhuman built their AI features, CEO Rahul Vohra wrote about the decision process in detail. “There was no shortage of ideas,” he wrote. Should they automatically summarize long emails? Prewrite drafts for you to review? All great ideas that all ended up being rejected. Vohra’s reasoning was that those features are all preemptive. The user sets them up once and they run automatically. Preemptive features cost more to run and must meet a higher quality bar. “Imagine if automatic summaries or prewritten drafts were low quality. You would tune them out, or just turn them off,” Vohra wrote. So they started with on-demand features instead.

I distinctly remember getting this email. Despite getting a daily drum beat of feature releases from my personal software suite, I remember admiring the choices they made, even though I didn’t necessarily think they had made the right one.

There is a temptation to be Steve Jobs with feature releases. You descend from the mountaintop, enrobed in black turtleneck of a product geniushood and tell your customers what they want. Unfortunately, you are not that guy. It is much better to show your customers you are human, the hard choices you struggled with, and where you landed. And again, this type of email is something an AI draft will never produce on its own, because AI was not in the room when you decided to ship one thing instead of another.

How to Actually Use AI to Do This

Everything above can be summarized in one sentence: good product writing contains information that only you know, written in a way that only you could write. The practical question is how to get that information out of your head and into the post, using AI tools, without the result reading like it was written by a chatbot with access to your Jira board.

Mess over spec. If you give Claude your release notes and say “write blog post good,” you will get a steaming pile of meh every time. Instead, give it all the background data, pulling in slack threads, customer support tickets that sparked the idea, etc. Then, ramble into it for five minutes in voice mode about why this blog posts matters in the context of the company. AI can put it all together better than you can.

Use AI to find your argument. Ask: “What is the strongest case for why we built this instead of the three other things we could have built?” Use the answer to find your angle. Then rewrite until it sounds like something you’d say to a smart friend. If you would be comfortable sending it as a board update without rewriting first, you’ve messed up. (Or your board is probably a little too chill).

Write ugly first. The best AI-assisted product writing starts with a terrible human draft, full of half-thoughts and run-on sentences, and uses AI to clean it up. This is the opposite of what most people do. Starting ugly and polishing with AI produces writing that sounds like a person. Starting clean and trying to add personality produces writing that sounds like a chatbot in a tophat.

Your company can write better than it currently is. Use this post to get started.

For more weekly dives into the world of early stage startups, subscribe below.

You are receiving this newsletter since you opted in earlier; if you would like to opt out of future newsletters, you can unsubscribe immediately.

This newsletter is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. You should consult your own advisers as to those matters. This newsletter may link to other websites and certain information contained herein has been obtained from third-party sources. While taken from sources believed to be reliable, a16z has not independently verified such information and makes no representations about the enduring accuracy of the information or its appropriateness for a given situation.

References to any companies, securities, or digital assets are for illustrative purposes only and do not constitute an investment recommendation or offer to provide investment advisory services. Any references to companies are for illustrative purposes only; please see a16z.com/investments. Furthermore, this content is not directed at nor intended for use by any investors or prospective investors, and may not under any circumstances be relied upon when making a decision to invest in any fund managed by a16z. (An offering to invest in an a16z fund will be made only by the private placement memorandum, subscription agreement, and other relevant documentation of any such fund which should be read in their entirety.) Past performance is not indicative of future results.

Charts and graphs provided within are for informational purposes solely and should not be relied upon when making any investment decision. Content in this newsletter speaks only as of the date indicated. Any projections, estimates, forecasts, targets, prospects and/or opinions expressed in these materials are subject to change without notice and may differ or be contrary to opinions expressed by others. Please see a16z.com/disclosures for additional important details.

Last September, the founders of 60 startups were sitting right where you are now, looking at a message inviting them to apply to join the next batch of a16z speedrun.

Last Monday, those same founders stepped onto the stage at the Palace of Fine Arts in San Francisco to pitch their companies to over 1,000 in the audience and over 10,000 viewers online.

As the first attendees attendees arrived, a16z’s Andrew Lee climbed up on a chair to rally the crowd.

Breakfast was served as founders set up their booths and chatted with guests.

Quickly, the main theater filled up with guests eager to kick off the day’s main event.

Demo Day presentations are intense: a back-to-back onslaught of 90-second pitches from the 60 speedrun companies from the class of SR006.

But the founders came prepared. Founders like Sam Oh of Concorda (shown below) had already done a test-run in this venue two weeks prior, during “Alumni Demo Day.”

The range among this year’s companies was wild: insurance solutions, next-gen entertainment apps, laundry-folding robots, and AI agents for just about everything.

Once the pitches wrapped, every founder had time at their booths to field questions.

Here, as onstage, all the practice and time spent building pays off when you see a founder walking an investor through the product for the first time, watching the lightbulb go on.

Some founders came ready to be remembered. Paypath’s team showed up in custom “Modern Debt Rebuilt” merch, just the kind of branding instinct that sticks in an investor’s memory at 6pm after 60 pitches.

That’s a wrap on SR006. If you’re building something interesting, apply to join SR007. We can’t wait to see you on that stage.

For more weekly dives into the world of early stage startups, subscribe below.

You are receiving this newsletter since you opted in earlier; if you would like to opt out of future newsletters, you can unsubscribe immediately.

This newsletter is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. You should consult your own advisers as to those matters. This newsletter may link to other websites and certain information contained herein has been obtained from third-party sources. While taken from sources believed to be reliable, a16z has not independently verified such information and makes no representations about the enduring accuracy of the information or its appropriateness for a given situation.

References to any companies, securities, or digital assets are for illustrative purposes only and do not constitute an investment recommendation or offer to provide investment advisory services. Any references to companies are for illustrative purposes only; please see a16z.com/investments. Furthermore, this content is not directed at nor intended for use by any investors or prospective investors, and may not under any circumstances be relied upon when making a decision to invest in any fund managed by a16z. (An offering to invest in an a16z fund will be made only by the private placement memorandum, subscription agreement, and other relevant documentation of any such fund which should be read in their entirety.) Past performance is not indicative of future results.

Charts and graphs provided within are for informational purposes solely and should not be relied upon when making any investment decision. Content in this newsletter speaks only as of the date indicated. Any projections, estimates, forecasts, targets, prospects and/or opinions expressed in these materials are subject to change without notice and may differ or be contrary to opinions expressed by others. Please see a16z.com/disclosures for additional important details.

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RSVP on Partiful using the links below to reserve your spot on one of the five days:

Monday (4/20) | Tuesday | Wednesday | Thursday | Friday (4/24)

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🏛️ Today is Demo Day for the class of SR006! We’ll be sharing lots of photos on our social accounts. Signups are closed for this one, but if you’d like to join us at the next Demo Day, register here.

💰 Shout out to Rork (SR005) on their $15M seed round!

🏋 Andrew Chen explained what the bar is to get into speedrun on a recent episode of George Bandarian’s Agentic Podcast

💼 Join our talent network for more opportunities. If we see a fit for you, we’ll intro you to relevant founders in the portfolio

Qasar Younis is the co-founder and CEO of Applied Intuition, a $15 billion AI software company for autonomous systems. Previously, Younis was an automotive engineer at General Motors, built two startups (the second acquired by Google, where he ended up reporting near the top of the org), and served as COO at Y Combinator.

In a fireside chat with a16z speedrun investing partner Kenan Saleh, Younis laid out how he thinks about decision-making, culture, recruiting, work ethic, and what it actually takes to sustain a company for the long haul. His philosophy, which he calls “radical pragmatism,” boils down to stripping emotion from decisions and refusing to borrow frameworks wholesale from anyone else, including him.

Scroll down for our top five takeaways from the conversation:

1. Don’t Borrow Other People’s Frameworks

Younis’s central philosophy is what he calls “radical pragmatism”—a term so core to his identity that radicalpragmatism.com literally redirects to his website. The idea came from years of watching smart people give confident advice that didn’t transfer. At YC, he was surrounded by successful CEOs who all had strong, often contradictory views on how companies should run, and it started to make him feel a little crazy. Applied Intuition, his third company, became the place where he could finally test his own instincts. The results gave him his sanity back.

“When you think about your company, you can’t take ideas from me or other people. You have to make decisions based on the reality of who you are as a person, who your co-founder is, the stage and the resources you have available, the state of your competitors and the state of the market.”

He drew an analogy to Bruce Lee, who studied every martial art and then created his own—one built for practical use, not tradition. Younis sees startup advice the same way: most of what gets said in interviews is seventy percent entertainment and thirty percent practical usability. “It’s like watching Breaking Bad for life advice,” he said. “High school teachers who get cancer just die. That’s the sad reality.”

This is to say: Take all the advice that follows with a grain of salt.

2. Compensate Against Your Values

When Applied Intuition was about a dozen people and had landed $10 million in business, Younis and his team went to a house in Santa Cruz on a Friday afternoon and wrote down why they thought they had early success. That became the company’s ten values—less a statement of aspiration than a forensic analysis of what was actually working. The hypothesis: as you grow to thirty, fifty, two hundred people, you regress to the mean. The values were meant to fight that.

“A lot of companies have values. So why do some companies maintain this very prickly shape where they’re so distinct? One of the key reasons is we compensate and we promote against adherence to our values. That’s what makes them actually real.”

The mechanism is specific: each of the ten values has roughly five observable behaviors underneath it—about fifty in total. Every individual contributor rates their manager on a one-to-five scale for each behavior, and you can’t pick three. Questions like “My manager is decisive,” “My manager is a good teacher,” “My manager is the most technically competent person on the team,” and even “My manager works harder than me.” When you ask a thousand engineers that last one, Younis pointed out, you find out very quickly which managers actually work hard—because answering “yes” means admitting you’re the lazier one.

3. Do the Opposite of What Big Companies Do

Younis has a simple heuristic that has shaped much of Applied Intuition’s culture: whatever large companies do, don’t do that. Big companies love org charts? Don’t have one until fifty people. Big companies love titles? No titles. Big companies love LinkedIn? No employee was on LinkedIn until five years into the company.

“We would have competitors—rest in peace—and I’d tell the recruiting team: go create the org chart for them. They would literally go to every one of their employees’ LinkedIn profiles, see their job titles, see what they’re doing, and reverse-engineer their org chart. And then it was like, if we can do that to them, they can probably do it to us. Everyone’s off LinkedIn.”

The no-titles policy also serves as a hiring filter: when someone interviewing is really title-oriented, that tells you something. Younis also kept his calendar public to the entire company for ninety-five percent of its history, as did his co-founder and leads. The logic: if your calendar isn’t full of product reviews and customer meetings, you should be embarrassed. “Shame is a great moral compass,” he said.

4. Raise Money as a Weapon, Even If You Never Spend It

One of the biggest things Younis said he’d changed his mind about is fundraising. He used to believe that if the company was genuinely great, everyone would just know. He now considers that a fantasy.

“I had this fantasy that if the company is really good, everyone’s going to know. They won’t. Raising money does send messages. It’s sending a very clear message to your employees, other investors, your competitors, and your customers that you’re doing well.”

Applied Intuition has raised a billion dollars and has never used any of it. The fundraising itself is the product: it’s a signal to the ecosystem, done at minimal dilution (about one percent in the last round). Younis was candid that this was a belief he had to be dragged into. He credited Marc Andreessen with pushing him to get the word out, telling him that nobody knew about this great company because of his “hermit-like view from Sunnyvale.”

Similarly, he begrudgingly admits that hyping your company matters.

“I hate to say it because I feel like I’m in middle school trying to get you to smoke or something. You’ve got to hype the company. But if I was sitting alone thinking, what do I believe today that I didn’t believe ten years ago? That’s one of them. I just felt like the good companies will get known. No.”

5. You Have to Enjoy It, or You Won’t Last

Younis has worked seven days a week since he was fourteen. And the companies Younis admires most—Berkshire Hathaway, Nvidia—are led by people who have been at it for decades. Jensen Huang has been CEO for thirty years. “A lot of people can do this for two or four years,” Younis said. “But to figure out how to do it while entire markets change and countries change and culture changes—that’s operating at the highest level.”

“One of our core values is “laugh a lot.” If you’re not having a good time and you’re not enjoying yourself, you’re not going to make it. You’re just not going to make it. The ego is such a powerful thing—you’ll rationalize all the reasons you want to give up.”

“This is a tough job,” Younis says. “You get phenomenal return for it. I still think, risk-adjusted, reward-adjusted, I would do this over Taco Bell every day of the week. That’s why I did it.”

That’s it for this week! Thanks to Qasar Younis for speaking with our founders.

For more weekly dives into the world of early stage startups, subscribe below.

You are receiving this newsletter since you opted in earlier; if you would like to opt out of future newsletters, you can unsubscribe immediately.

This newsletter is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. You should consult your own advisers as to those matters. This newsletter may link to other websites and certain information contained herein has been obtained from third-party sources. While taken from sources believed to be reliable, a16z has not independently verified such information and makes no representations about the enduring accuracy of the information or its appropriateness for a given situation.

References to any companies, securities, or digital assets are for illustrative purposes only and do not constitute an investment recommendation or offer to provide investment advisory services. Any references to companies are for illustrative purposes only; please see a16z.com/investments. Furthermore, this content is not directed at nor intended for use by any investors or prospective investors, and may not under any circumstances be relied upon when making a decision to invest in any fund managed by a16z. (An offering to invest in an a16z fund will be made only by the private placement memorandum, subscription agreement, and other relevant documentation of any such fund which should be read in their entirety.) Past performance is not indicative of future results.

Charts and graphs provided within are for informational purposes solely and should not be relied upon when making any investment decision. Content in this newsletter speaks only as of the date indicated. Any projections, estimates, forecasts, targets, prospects and/or opinions expressed in these materials are subject to change without notice and may differ or be contrary to opinions expressed by others. Please see a16z.com/disclosures for additional important details.

SPEEDRUN APPLICATIONS ARE OPENING SOON! And we’re coming to SF.

Join us at the pop-up speedrun cafe (presented by Mercury) in SF during the first week of the SR007 application window: April 20th–24th! Each guest can snag a drink, a food item, and a limited-edition hat (while supplies last).

RSVP on Partiful using the links below to reserve your spot on one of the five days:

Monday (4/20) | Tuesday | Wednesday | Thursday | Friday (4/24)

This Week’s Big Ideas 💡

💻 Andrew Chen comments on the growing wave of non-technical founders using AI coding tools to build companies: “their iteration speed is 10x.”

🪞 Mirror Mirror AI (SR006) founder Yusan Lin explains why she’s building infrastructure for people to own their own likenesses in the AI era.

🛠️ Bella Nazzari explores job openings for the growing discipline of “gtm engineering.”

💼 Join our talent network for more opportunities. If we see a fit for you, we’ll intro you to relevant founders in the portfolio

Every founder is trying to crack distribution. They’re posting on X, debating whether to start a podcast, and wondering if doing the latest viral trend on TikTok is worth the effort.

Meanwhile, LinkedIn is sitting right there—wildly underutilized and practically begging early-stage founders to use it. Eventually, this channel will be saturated like everything else. But for now, for the willing founder, we believe there are customers to be had.

The LinkedIn meta is driven by two factors:

• The audience is already there, pre-qualified. Every other social media fight is a slugfest between political takes, culture war brainrot, an algorithm that changes weekly, while you’re earnestly posting about your latest feature. In contrast, LinkedIn’s feed is overwhelmingly professional. The people scrolling it are decision-makers, investors, hiring managers, and operators looking for “work” content. If you’re selling to businesses or raising money, your buyers are literally browsing between meetings. manager.

• The algorithm is generous. LinkedIn’s distribution is still in growth mode. A post from a 7,000-follower account can get 850 likes and 184 comments—that’s what happened when Salar Shahini of Sweatpals (SR004) announced his team’s $12M raise. That’s a 12%+ engagement rate! The platform actively rewards original posts, especially from personal accounts (not company pages).

What actually works on LinkedIn

After watching hundreds of founders go through speedrun, here are some tips for making performant posts:

Post your actual numbers.

The highest-performing LinkedIn posts from speedrun founders are almost always the ones sharing real metrics. No one wants to read your thoughtslop pieces about vibe coding. Just follow the example of Daniel Dhawan of Rork (SR005)—he posted that Rork users had created over 500,000 projects with 2,000+ apps published to the App Store, hitting #2 in the US Dev Tools category” and let the numbers do the work. Specificity is the currency of trust on LinkedIn. Vague “excited to announce” posts get polite likes from your mother. Actual numbers get inbound leads.

Build in public, but make it a narrative.

Taylor Offer of Atrios (SR005) makes each post build the narrative around his company. He posts about the emotional arc of founding (”Don’t forget how bad you wanted what you currently have” got 44,000+ likes), the tactical realities of scaling, and meta-observations about the platform itself. His audience feels like they’re following a character in a show. Treat LinkedIn as a serialized story to build the kind of following that actually converts into quality leads. As we’ve discussed before, early sales is about people loving the founders first and the product second.

Use your pre-founder credibility.

Your career before your startup is a feature, not baggage. Eric Berman of Lil Snack (SR002) was a Hulu and Crunchyroll executive before founding an AI gaming company. Paddy Lambros of Dex (SR005) ran talent at Atomico, so when he posts about building an AI recruiter, his network of recruiters and hiring managers actually believes what he says. If you spent years in an industry before founding a company in that space, your LinkedIn network is your first customer list.

Don’t overthink the format.

The posts getting the most engagement from speedrun founders are almost comically simple. A photo with a short story. A screenshot of a metric. Michael Lingelbach of Hedra (SR002) posts about AI video breakthroughs in a few short paragraphs—no carousels, no “10 things I learned” threads, or graphic design. His $32M Series A announcement was straightforward and still generated dozens of comments from exactly the audience Hedra wants. LinkedIn rewards “authenticity” over production value. A real photo from your office beats a Canva graphic every time.

How to survive the trough of cringe

Let’s be very clear: the first few LinkedIn posts feel terrible. You’ll write something, hover over the post button, and wonder if your college roommate or former boss is going to think you’ve lost your mind. Call it the “trough of cringe.” Every founder who’s now crushing it on LinkedIn went through it.

The discomfort is a competitive advantage. It’s the barrier that keeps your competitors from doing this. If posting on LinkedIn felt natural and easy, everyone would do it and it wouldn’t work. So start with what you know is true. Write about something you genuinely experienced this week: a customer interaction, a technical decision, a number that surprised you. The bar for “good LinkedIn content” is lower than you think because most people aren’t posting anything at all.

The cringe fades. And unlike paid ads or PR agencies, it’s free. The only cost is your willingness to hit “post.”

That’s it for this week!

For more weekly dives into the world of early stage startups, subscribe below.

You are receiving this newsletter since you opted in earlier; if you would like to opt out of future newsletters, you can unsubscribe immediately.

This newsletter is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. You should consult your own advisers as to those matters. This newsletter may link to other websites and certain information contained herein has been obtained from third-party sources. While taken from sources believed to be reliable, a16z has not independently verified such information and makes no representations about the enduring accuracy of the information or its appropriateness for a given situation.

References to any companies, securities, or digital assets are for illustrative purposes only and do not constitute an investment recommendation or offer to provide investment advisory services. Any references to companies are for illustrative purposes only; please see a16z.com/investments. Furthermore, this content is not directed at nor intended for use by any investors or prospective investors, and may not under any circumstances be relied upon when making a decision to invest in any fund managed by a16z. (An offering to invest in an a16z fund will be made only by the private placement memorandum, subscription agreement, and other relevant documentation of any such fund which should be read in their entirety.) Past performance is not indicative of future results.

Charts and graphs provided within are for informational purposes solely and should not be relied upon when making any investment decision. Content in this newsletter speaks only as of the date indicated. Any projections, estimates, forecasts, targets, prospects and/or opinions expressed in these materials are subject to change without notice and may differ or be contrary to opinions expressed by others. Please see a16z.com/disclosures for additional important details.

Liquid Death is a healthy beverage company that looks like a beer brand, markets like an entertainment company, and grows like a tech startup. Founded in 2019 by Mike Cessario, a former ad creative with a background in making funny videos on no budget, the company has expanded from water to sparkling water, iced tea, and now energy drinks, doing hundreds of millions in revenue along the way. The company ran a Super Bowl ad this year which they produced internally for $300,000.

In a conversation with a16z speedrun, Cessario laid out the thinking behind the brand: why he assumes every product is a commodity, why comedy is the last unoccupied competitive moat in consumer goods, and what it actually takes to get a can of water onto a shelf at Kroger. Most of his advice applies far beyond beverages.

Watch the full conversation below, or scroll down for our top five takeaways from the conversation:

1. Comedy Is the One Thing Coke and Pepsi Can’t Do

Cessario’s career started in ad creative, and he’s always had a knack for making people laugh. He built Liquid Death’s competitive strategy around humor and entertainment in part because it’s structurally inaccessible to the biggest players in the market.

“Let’s say you want to do athlete marketing. Anybody with a checkbook can buy any athlete they want. If you’ve got the big enough number, you can get any snowboarder, any NFL athlete. So if you try to have a sports marketing theme for your brand, you’re just competing with every other giant brand that can just spend way more money than you can to, to, to buy more athletes or whatever. Comedy is the one thing that Coke and Pepsi can’t really do. Comedy is the one thing that Coke and Pepsi can’t really do. Even if they wanted to, true comedy can’t really survive in that bureaucracy.”

Cessario pointed to the experience of A-list comedians who’ve done deals with major brands, like Ben Stiller doing a Pepsi campaign. The story is always the same: everything funny got killed in the approval chain. “You actually had to work to make this person not funny,” he said.

2. Start by Assuming Your Product Is a Commodity

Cessario’s framework for thinking about brand starts from a premise that most founders resist: your product is probably not that different from your competitors’. He argued that founders get so deep in the weeds that they overweight tiny product differences that the broader market doesn’t notice or care about.

“Does Nike ever talk about how its materials last twenty days longer than Adidas? Any mustard on the shelf is probably all the same f***ing mustard. Can anybody pick out their favorite beer in a blind taste test? Probably not.”

His advice: start from the assumption that product differences are slim to none, then figure out how you win. Either you win on price and become the cheapest option, or you win because your commodity is far more memorable than everyone else’s. This thought exercise, he argued, is what forces you to invest in the things that actually create differentiation: brand, entertainment, and emotional connection.

3. An Entertainment Company That Monetizes via Beverage

Cessario described Liquid Death’s model inspired by the Red Bull playbook, with one substitution: comedy instead of action sports. The ethos is entertain people first, sell beverages second. That’s not a tagline. It’s the operational reality of how the company allocates resources.

“I made a video for fifteen hundred bucks that got three million views and generated more page followers than Aquafina with almost no investment. That’s proving out the model: if you can entertain people in commoditized categories, you’re going to have this huge competitive advantage because no one has any real product advantage.”

The economics have held at scale. Liquid Death’s Super Bowl ad cost $300,000 to produce internally, much lower than industry averages.

“We’re trying to make people laugh on the internet. As long as you can do that, you’re going to attract people and they have a reason to tune in. We’re occupying a place in their mind when they have five seconds to choose what to buy walking down the aisle.”

4. Cool Company, Not Just Cool Product

Asked to define what brand actually means, Cessario drew a distinction most founders miss. A lot of products are cool. Very few companies are cool. The strongest brands are the ones where people think the company itself is cool, independent of any specific product.

“There’s a lot of really cool products out there. But there’s very few cool companies. If you ask people, ‘What’s a really cool company?’ That’s where you start getting down to the people who are really good at brand.”

He used ChatGPT as a current example. Every LLM does more or less the same thing. But one brand dominates because it occupies a place in people’s heads, the way Google did with search.

Cessario also pushed back on the idea that mission alone drives loyalty. He told the story of an Uber driver who fell in love with Liquid Death’s “death to plastic” message. But the real reason she’d keep buying, he argued, is that the can gives her permission to participate in a counterculture she wouldn’t otherwise access. The mission is how she justifies it. “If that were really the only reason, the minute there was canned Smartwater, she’d buy that because it was cheaper.”

5. Distribution Is the Real Challenge

For founders who’ve only operated in software, Cessario’s description of beverage distribution is a wake-up call. Getting authorized in a retail chain is relatively straightforward. One meeting with a Walmart buyer can open four thousand doors. The problem is what happens next.

“As a small brand, you’re authorized in two thousand Krogers, but you’re only on the shelf in seven hundred, because the distributors just aren’t actually getting the product to the retailer. They don’t care, and there’s nothing you can do about it.”

The beverage industry runs on DSD (direct store delivery) networks owned by Coke, Pepsi, and the beer companies. You can’t use Coke’s or Pepsi’s distribution unless they own you. The beer networks are different because of the three-tier system: alcohol laws prevent producers from owning more than twenty percent of their distribution. So hundreds of independent distributors exist, and a new brand has to win them over one by one.

But even then, it’s a challenge to get distributors to get you priority:

“As a new brand, you’ve got to go one by one to all these guys and convince them to distribute your product ,to take your product and sell it to Walmart and Target and Kroger and 7-Eleven and everywhere else. But they’re also selling Budweiser and Bud Light and Michelob Ultra and all these other brands. So when you go in as a small brand, you’re so far down the totem pole. The rep is going into a Kroger and he’s only going to be there an hour. He needs to go to the next store. Most of his time is going to be restocking Bud Light.”

This, says Cessario, is why managing distribution is far and away the hardest part of scaling a new ready-to-drink beverage company.

Thanks to Mike Cessario for sharing his insights with us. And for more weekly dives into the world of early stage startups, subscribe below.

You are receiving this newsletter since you opted in earlier; if you would like to opt out of future newsletters, you can unsubscribe immediately.

This newsletter is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. You should consult your own advisers as to those matters. This newsletter may link to other websites and certain information contained herein has been obtained from third-party sources. While taken from sources believed to be reliable, a16z has not independently verified such information and makes no representations about the enduring accuracy of the information or its appropriateness for a given situation.

References to any companies, securities, or digital assets are for illustrative purposes only and do not constitute an investment recommendation or offer to provide investment advisory services. Any references to companies are for illustrative purposes only; please see a16z.com/investments. Furthermore, this content is not directed at nor intended for use by any investors or prospective investors, and may not under any circumstances be relied upon when making a decision to invest in any fund managed by a16z. (An offering to invest in an a16z fund will be made only by the private placement memorandum, subscription agreement, and other relevant documentation of any such fund which should be read in their entirety.) Past performance is not indicative of future results.

Charts and graphs provided within are for informational purposes solely and should not be relied upon when making any investment decision. Content in this newsletter speaks only as of the date indicated. Any projections, estimates, forecasts, targets, prospects and/or opinions expressed in these materials are subject to change without notice and may differ or be contrary to opinions expressed by others. Please see a16z.com/disclosures for additional important details.

🏰 Jon Lai proposes the “minimum viable moat” as the way to win in AI

🤖 Andrew Chen has a simple rubric for telling the difference between AI-native products and products with AI bolted on as an afterthought

💰 Emily Bennett has advice on fundraising: don’t lead with your “dream investor.”

💼 Join our talent network for more opportunities. If we see a fit for you, we’ll intro you to relevant founders in the portfolio

Somewhere around 2003, in a room full of investors, a video game crashed.

The game was called Republic: The Revolution, and it was supposed to be a generation-defining political simulation. Its creator, a young Londoner named Demis Hassabis, had pitched it with the kind of total conviction that makes people open their checkbooks. The demo failed. The product barely functioned. But Hassabis forged ahead, telling investors a story about what the game would become.

Ultimately, the game shipped to middling reviews, and Hassabis’s company, Elixir Studios, folded. Hassabis went quiet for a few years, then started a small research lab called DeepMind. Everyone in Silicon Valley knows the story from here. Google acquired DeepMind and the company has gone on to develop technologies that power Google’s frontier AI models, and which have earned Hassabis the Nobel Prize in Chemistry.

Sebastian Mallaby has been writing about entrepreneurs like Hassabis for twenty years. His book More Money Than God went inside hedge funds, The Power Law chronicled venture capital, and his new book, The Infinity Machine, tells the story of Hassabis and, through him, the story of how modern AI came to exist.

We spoke with Mallaby about what he’s observed across all three of these worlds, and why the Hassabis story might be more useful to founders than they realize.

Conviction Vs Delusion

Hedge funds, startups, venture capital: in each case, a small group of people has decided that everyone else has it wrong, and is betting real money on that belief. These are all fields where the gap between conviction and delusion is essentially invisible from the outside. The only thing that separates them is the outcome.

We asked Mallaby: Is this tension between conviction and delusion the real throughline connecting your work?

“I think that’s a fair characterization of the whole investment boutique entrepreneurship ecosystem,” Mallaby said. “In hedge funds, you’ve got market prices which you think you can outguess, and those market prices are the weighted average of intelligent people’s judgment. So you need to be quite bold to think you know better. In the same way, a startup entrepreneur is trying to disrupt incumbents who are not idiots. You have to be bold.”

But the line between conviction and delusion can at times appear thin. And as Mallaby tells it, even the most successful founders have found themselves on both sides of that line.

The Fluency Test

One of the early stories told in The Infinity Machine recounts how the dev team on Republic: The Revolution slipped into a pattern of delusional belief about the game’s chances at success. “The engineers knew he [Hassabis] wouldn’t accept anything short of ‘yes, we can do this,’” Mallaby told us. “So they said that. And that made Hassabis even more determined not to accept no for an answer. Because he was hearing yes from his own team, he got even more confident. There was this feedback loop.”

What matters about this story is what happened after. Mallaby frames the Elixir collapse as the event that made DeepMind possible.

Years later, facing a similar crossroads with AlphaFold, Hassabis found himself in the position of deciding whether to push a team past the point where its own leader said the goal was impossible. The head of the AlphaFold effort, Andrew Senior, told him flatly in 2018: we’ve built the best protein-folding system in the world, but we cannot do what you’re asking us to do. Instead of overriding him, Hassabis began sitting in on meetings with the broader team and listening closely for what Mallaby calls “the fluency of the conversation.”

“If lots of ideas are coming up, he figures, well, it’s not like they’re stuck,” Mallaby says. “If they had more time or resources, they could test out some of these ideas they’re kicking around in the conference room. Fluency was his metric for whether to go ahead.”

A room full of people generating ideas looks fundamentally different from a room that’s gone quiet. The first means there’s potential. The latter means the problem might be a dead end. The fluency test was how Hassabis learned to tell the difference, and it was a lesson hard-won by a founder who’d experienced the downsides of charging ahead when the room was telling him what he wanted to hear.

Mallaby put the takeaway plainly: “I think it’ll resonate with a venture capital firm that second-time entrepreneurs are often the ones you most want to back.”

On Communicating Conviction

For many practical and structural reasons, the dominant way that Silicon Valley founders talk is prospective. You announce what you’re going to build before you’ve built it. You generate excitement around a future state that may or may not arrive. Some of the most visible figures in tech have operated this way for years, tweeting about ambitious new capabilities before the technology can deliver them. It works as a fundraising mechanism. It also, as Mallaby noted dryly, sometimes involves announcing things that aren’t yet certain to work.

Hassabis, at least in his mature period, worked in the opposite direction. After DeepMind’s Atari system started producing real results in 2013, his instinct was to take the concrete achievement and wring every possible drop of credibility out of it. The target he picked was Nature magazine. “Nobody else on his team thought that publishing a paper in Nature was even conceivable,” Mallaby said. “Nature didn’t really do computer science. But Hassabis cultivated an editor at Nature for a year, then got him to agree to look at a submission from DeepMind, then got the DeepMind video team to design cover art so Nature would put it on the front.”

These kinds of details accumulate throughout the book. Hassabis comes across as someone who wastes very little, who finds a use for whatever’s already lying around, and who treats reputation as a resource to be deployed strategically rather than as a mere byproduct of the work.

“He was absolutely as focused on communication as anyone else in AI,” Mallaby said. “But he had this retrospective approach, of playing up actual achievements, as opposed to announcing future ones.”

On Timing and “Scientific Taste”

Marc Andreessen likes to say that one of the main reasons great entrepreneurs fail isn’t because their idea is wrong, but because they were simply too early. Predicting when the market is ready for something is one of the hardest jobs of the entrepreneur, and a thread running through Mallaby’s book is that Hassabis foresaw a lot of things before others, including the possibilities of reinforcement learning and the possibility of delivering something meaningful for the protein folding problem.

Mallaby told us that Hassabis uses the phrase “scientific taste” to describe the ability to sense when a field is about to tip, even when most observers still see stagnation. It’s a phrase that does a lot of quiet work, treating taste as pattern recognition operating at the boundary between what the data supports and what it merely suggests: the ability to read straws in the wind when everyone else is staring at the ground.

“With DeepMind’s Atari agent, which is an early experiment in combining deep learning with reinforcement learning, Hassabis sees when something is poised to advance,” Mallaby said. “And then he repeats the same trick with the decision to go after AlphaGo, even though Sergey Brin had told him it’s crazy. After Atari he feels you can do Go. Later, after Go, he feels you can do protein folding.”

David Silver, one of DeepMind’s key researchers, gave Mallaby a metaphor for this: Hassabis had understood “the ladder.” Each project was grander than the last, and each one funded the next: financially, and in terms of credibility. To get to the moon, the DeepMind team figured out which rung to stand on next.

Internally, the DeepMind team ran two modes at once: a cheap exploration layer, where researchers pursued open-ended questions, and an expensive exploitation layer, where strike teams poured everything into a single target. Hassabis’s job, as Mallaby described it, was knowing when to shift from one to the other. “He’s willing to have people exploring different avenues for AI, doing their thing,” Mallaby said. “But then he’s going to have the scientific taste to know which one to push on. And when he’s pushing, it’s a totally different organizational structure.”

How to Predict the Future

We asked Mallaby whether, after spending years embedded in this story, he felt he understood where AI was actually going. He gave a modest yes.

“My view is, if you look at what’s happened since ChatGPT came out, the number of major jumps that the technology has made is flabbergasting,” he said. “You go from something which basically hallucinated nonstop to something that pretty much got that under control. Longer context windows. Multimodal. Reasoning. Now it’s starting to be agentic. Next is world models. And it’s only been three and a half years.”

Every time someone declares a ceiling, Mallaby pointed out, a new axis of scaling appears to replace the one that supposedly ran out. He’s bullish on infrastructure. The application layer, he admitted, is anyone’s guess.

But the question we kept circling back to was the one about conviction and delusion, and whether there was any reliable way to tell them apart before the outcome settles the matter. Mallaby’s answer, when it finally came, had the weight of someone who has spent two decades in rooms with people who stake everything on their own judgment.

“You don’t necessarily get the balance correct the first time,” he said. “But the only way you learn is by doing.”

The Elixir game crashed, and the company died, and then the same person started something else.

Thanks to Sebastian Mallaby for speaking with us. And for more weekly dives into the world of early stage startups, subscribe below.

You are receiving this newsletter since you opted in earlier; if you would like to opt out of future newsletters, you can unsubscribe immediately.

This newsletter is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. You should consult your own advisers as to those matters. This newsletter may link to other websites and certain information contained herein has been obtained from third-party sources. While taken from sources believed to be reliable, a16z has not independently verified such information and makes no representations about the enduring accuracy of the information or its appropriateness for a given situation.

References to any companies, securities, or digital assets are for illustrative purposes only and do not constitute an investment recommendation or offer to provide investment advisory services. Any references to companies are for illustrative purposes only; please see a16z.com/investments. Furthermore, this content is not directed at nor intended for use by any investors or prospective investors, and may not under any circumstances be relied upon when making a decision to invest in any fund managed by a16z. (An offering to invest in an a16z fund will be made only by the private placement memorandum, subscription agreement, and other relevant documentation of any such fund which should be read in their entirety.) Past performance is not indicative of future results.

Charts and graphs provided within are for informational purposes solely and should not be relied upon when making any investment decision. Content in this newsletter speaks only as of the date indicated. Any projections, estimates, forecasts, targets, prospects and/or opinions expressed in these materials are subject to change without notice and may differ or be contrary to opinions expressed by others. Please see a16z.com/disclosures for additional important details.

📈 We’re hiring a Marketing Partner to support our new Alpha fellowship program! See Katia Ameri’s post here for details.

🚀 As SR006 Demo Day approaches more founders are coming out of stealth like Audrey Lo, who’s building AI caretakers for seniors; Yusan Lin, who’s building a marketplace for fashion models to license their likenesses; and Ruming Zhen, who’s building AI agents for real-world context.

🔎 Bella Nazzari says using Claude to mass-apply to jobs isn’t likely to work. But she has a method that will.

💼 Join our talent network for more opportunities. If we see a fit for you, we’ll intro you to relevant founders in the portfolio

Rahul Vohra learned how to make things fun before he learned how to make them useful. He started his career as a game designer on RuneScape, created the Gmail plugin Rapportive (acquired by LinkedIn), and then spent three years building Superhuman before letting the public anywhere near it. Along the way, he developed a widely shared framework for measuring product-market fit.

In a fireside chat with a16z speedrun Visiting Partner Fareed Mosavat, Vohra laid out the playbook behind Superhuman’s rise. We discussed why gamification fails but game design works, why he turned away customers who wanted to pay him, and why the right price for email is thirty dollars a month.

Watch the full conversation below, or scroll down for our top five takeaways from the conversation.

1. The Product Market Fit Engine

By April 2017, Superhuman was two or three years into development and the team was pushing hard to launch. Vohra suspected the product would flop. But “we don’t have product-market fit, keep working” is not an inspiring message. So he built a system to fix it and rally the team around the process.

The foundation was a question from growth pioneer Sean Ellis: “How would you feel if you could no longer use the product?” Users answer one of “not disappointed, somewhat disappointed, or very disappointed.” Ellis benchmarked hundreds of startups and found that companies reaching product-market fit almost always had more than 40% say they’d be “very disappointed” to lose access to the product. Companies that didn’t almost always had less.

Vohra decided to apply this framework to Superhuman:

“I ran the first question and we had twenty-two percent very disappointed. Way less than forty. You might think I was bummed out. Actually, I was excited. Finally, I could explain what I was feeling to the team in a way that was irreproachable. You can’t argue with these metrics.”

Vohra’s added three questions of his own: Who is the product best for? What’s the main benefit? How can we improve it? The first move was changing the market, not the product. By dropping non-core personas (data science, sales, engineering) and focusing on VCs, CEOs, founders, and BD, the score jumped from twenty-two to thirty-two percent with zero product changes.

Then he focused on the “somewhat disappointed” users for whom the main benefit already resonated. Only a few things were holding them back. He worked down that list systematically, splitting energy between building more of what users loved and fixing the boring complaints. Vohra reports on the results:

“The quarter after, we were at forty-six percent. The quarter after that, fifty-six percent. The quarter after that, fifty-eight percent.”

2. You Have the Right to Deny Service

Superhuman didn’t have an Android app for years. It lacked an Outlook integration and a Salesforce connector. Rather than let those gaps create detractors, Vohra simply didn’t let those people in. He screened users with a survey before they could sign up.

“We’d be like, what mobile phone do you have? They’d say Android. And I said, well, you can’t have Superhuman. And people would get confused. Like, why isn’t it my decision whether or not I buy? And I’m like, no, it’s my decision whether or not I sell.”

The logic was straightforward: every user who has a bad experience is a net detractor. Controlling who gets in means controlling the narrative around your product. Vohra’s goal was to make sure every single person who used Superhuman became a net promoter. That meant being willing to say no to people who wanted to give him money.

3. Game Design vs. Gamification

Vohra started his career as a game designer on RuneScape, and he brought those instincts directly into Superhuman. But he drew a sharp line between game design and gamification. Points, badges, streaks, and leaderboards can push behavior. They don’t make the underlying thing fun.

He cited a Stanford study from the 1970s. Researchers divided kids into two groups: one promised a reward for drawing, the other given no incentive. Over the following days, the rewarded kids spent half as much time drawing. The extrinsic motivator killed the intrinsic motivation.

“That’s exactly what happens with gamification. Giving your users a reward for something can reduce their intrinsic motivation to do that thing. To build products that feel like a game, you have to go into the theory of game design: what is a game, what is play, what is fun?”

His approach centers on building “toys” within the product. A toy invites playful exploration. Superhuman’s time autocompleter is his go-to example: users type “2D” for two days, “3MO” for three months, then start trying to break it. Someone typed “never.” The product responded with a shrug emoji. These localized moments of delight, built on what Vohra calls “squishy affordances,” are the foundation of a product that people genuinely enjoy using.

4. The Human-Touch Onboarding Machine

For years, Vohra personally onboarded every new Superhuman user. Five people a week, two-hour sessions, in person at their office. He’d research them beforehand, bring a gift (whiskey, wine, or tea), watch them use Gmail, demo Superhuman, ask for their credit card, then observe them using the product for as long as they’d let him.

“If you haven’t done this, please do it. And please never stop doing it. Even with a mature product, it is incredible how much you will see that maybe even your product engineers or your PMs won’t see. You as the founder are going to see every single problem.”

The team pushed him to grow faster. He refused until every bug from those sessions was fixed. “Every user has bug fatigue. They might tell you one or two or three bugs. They’re not going to tell you ten or twenty or thirty. And we definitely had that many.”

Then the metrics came in: activation, retention, virality, and NPS were all off the charts. Vohra tested whether it was him or the process by having his brother (then head of growth) run the onboardings. His brother was even better, so it was the process. That’s when Vohra hired onboarding specialists in pairs, scaled to forty Zoom calls a week, and turned it into a machine. Investors saw this approach as a genuine strategic edge.

5. Premium Pricing and the Prosumer

Superhuman launched at $30 per month for email. Vohra deliberately onboarded the five most influential people he could find each week, and he priced the product to match how those people think about themselves.

“Email is kind of part of the ego. It’s like, ‘Oh yeah, I get this many emails a week.’ The pressure is part of the ego. And I was like, well, if that’s the case, you know what’s going to make you feel good about it? Spending a lot of money on fixing that problem.”

He framed the broader strategy as the “prosumerization of the enterprise.” A prosumer, in his definition, is a power user with all the economic agency but none of the time. They have the money to spend on solving a problem; they just don’t have the patience to figure things out. That’s the customer Superhuman was built for.

His one regret on pricing: not raising it sooner. Superhuman stayed at $30 per month for years before adding a $40 tier. Vohra estimated they left 30% of ARR on the table. His tactical advice to founders: raise prices every year to stay ahead of inflation.

Thanks to Rahul Vohra for sharing his insights with our founders. And for more weekly dives into the world of early stage startups, subscribe below.

You are receiving this newsletter since you opted in earlier; if you would like to opt out of future newsletters, you can unsubscribe immediately.

This newsletter is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. You should consult your own advisers as to those matters. This newsletter may link to other websites and certain information contained herein has been obtained from third-party sources. While taken from sources believed to be reliable, a16z has not independently verified such information and makes no representations about the enduring accuracy of the information or its appropriateness for a given situation.

References to any companies, securities, or digital assets are for illustrative purposes only and do not constitute an investment recommendation or offer to provide investment advisory services. Any references to companies are for illustrative purposes only; please see a16z.com/investments. Furthermore, this content is not directed at nor intended for use by any investors or prospective investors, and may not under any circumstances be relied upon when making a decision to invest in any fund managed by a16z. (An offering to invest in an a16z fund will be made only by the private placement memorandum, subscription agreement, and other relevant documentation of any such fund which should be read in their entirety.) Past performance is not indicative of future results.

Charts and graphs provided within are for informational purposes solely and should not be relied upon when making any investment decision. Content in this newsletter speaks only as of the date indicated. Any projections, estimates, forecasts, targets, prospects and/or opinions expressed in these materials are subject to change without notice and may differ or be contrary to opinions expressed by others. Please see a16z.com/disclosures for additional important details.

We're gearing up for New York Tech Week (June 1-7), and we want you to host an event. If you've been wanting to throw a founder dinner, a demo day, a hiring happy hour, or really anything that gets great people in a room together, this is your moment.

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This week’s essay is a guest post from a16z speedrun investor Marcus Segal. He draws on his decades of startup experience to offer some time-tested advice on seeking, and keeping, product-market fit.

Emmett Shear, the co-founder of Twitch, visited speedrun founders for a session recently. Someone asked him how he would describe product-market fit. His answer, “How do you describe being in love? You know it when you’re in love.”

Fair enough. But the job of a founder isn’t to sit around waiting to fall in love. The job is to put your best foot forward and to avoid looking for love in all the wrong places. And the combination of a team of engineers cranking out features with AI, a lack of vision for your product and an undisciplined feature list is exactly that—looking for love everywhere all at once with a bad haircut!

When I was at Zynga I was fortunate enough to work closely with Mark Pincus—a founder that had never shipped a game—to build one of the biggest gaming companies on Earth with 300M players. Along the way I’ve co-founded two other startups in B2B and B2C and had the opportunity to support and learn from hundreds of founders on their quests for PMF while mentoring at Y Combinator, Google Launchpad, and now as an investor on the a16z speedrun team.

Across all of these experiences and through massive disruptions in technology three things have never changed:

1. A CEO’s job is to not run out of money before finding PMF

2. Engineering person hours are the most important resource in your company

3. Finding and keeping PMF is more likely to occur with a roadmapping process

It is my hope to share what I have seen work at Zynga and countless other startups in the hopes that all of you can find PMF.

PMF Is a Journey, Not a Destination

When I joined Zynga, none of us really knew how to make great games. What Mark Pincus understood, though, was how to build a system for finding what works—fast.

Our competitors released content once every two weeks, in English. We released five to ten content updates per week, per game, in 26 languages. We didn’t have AI. We generated an enormous number of hypotheses that could be rapidly tested and threw an army of PM’s,engineers, artists and LOTS of QA onto anything that found heat. The work of a 40 or 50 person team at Zynga could now be done with 10 people.

The methodology we used at Zynga wasn’t complicated. The best processes rarely are. Here’s the version I recommend at speedrun—adapted for teams that are building with AI tools to iterate on live products to deliver results faster and better.

Start with the metric, then build the feature.

Before you create a single line of code for a new feature, answer one question: what number are you trying to move? Reach? Retention? Revenue? The specific metric doesn’t matter as much as the discipline of choosing one. Because if you can’t articulate which number a feature is supposed to move, you have no way of knowing whether it worked or was accretive to the product experience. It should be one sentence, “We will launch Product X feature to give Y value to the customer moving Z metric.”

Get all the ideas out, then stack rank them.

This is where most founders stall or face major coordination breakdowns on their teams. All the builders have a running list of features in their heads and they build whatever feels most urgent on any given day. Don’t do that. Start by getting every idea out of your heads and onto a list. Then rank them as a team by asking a simple question: which of these has the highest probability of moving the metric we care about?

T-shirt size the effort.

Vibe coding has broken our intuitions about how long things take to build, particularly across teams.. Pre-AI, experienced engineers got pretty good at estimating effort. Now the volume of code generated across a team of engineers creates new layers of complexity in coordination and design (to name a few).

Things that seemed trivial take forever to polish, and things that seemed hard take twenty minutes and merging everything into a thoughtfully designed UI/UX framework is tougher than ever. And let’s not forget We all need to build or rebuild this muscle for the AI era so estimate and track actuals. It’s a new skill so expect a lot of learning along the way.

Power rank by impact-to-effort.

Now you have a list of features, ranked by expected impact, with effort estimates attached. The math practically does itself. High impact, low effort? Do it first. Low impact, high effort? Maybe never.

Roadmap looking one-week-back, one-week-forwards view.

At Zynga, we looked one week back and three weeks forward every week in a team review. What did we build last week? What did we think would happen? What actually happened? The metrics provided the answers. MVP’s of features were tested and scrapped if they did not perform. Course corrections happened to the roadmap to avoid wasting engineering time. Learning compounded quickly and spread across all of our games.

With today’s tools that cadence would be way too slow. Today we look one-week-back and one week forward. The cadence matters. It’s short enough to course-correct fast, but long enough to actually ship meaningful work.

Measure everything.

At every successful startup or scale up I have seen up close the winners are obsessed with metrics. Great ideas can come from any person in your organization.If someone on the team pitches or builds a feature and accurately predicts what it will do they should be lauded. If they are wrong, nobody gets fired. The next time, they will calibrate better. That’s the culture you need. Experience is never wasted if your team learns and gets better.

The Gift

Here’s what I want founders to take away from this: I believe a deliberate roadmapping process is the highest-leverage activity available to you as a founder to increase your chances of finding and keeping PMF. You will maximize your most valuable resource engineering time and grow a killer team in the process.

Enjoy the journey.

Got questions for Marcus? Let us know in the comments. And for more weekly dives into the world of early stage startups, subscribe below.

You are receiving this newsletter since you opted in earlier; if you would like to opt out of future newsletters, you can unsubscribe immediately.

This newsletter is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. You should consult your own advisers as to those matters. This newsletter may link to other websites and certain information contained herein has been obtained from third-party sources. While taken from sources believed to be reliable, a16z has not independently verified such information and makes no representations about the enduring accuracy of the information or its appropriateness for a given situation.

References to any companies, securities, or digital assets are for illustrative purposes only and do not constitute an investment recommendation or offer to provide investment advisory services. Any references to companies are for illustrative purposes only; please see a16z.com/investments. Furthermore, this content is not directed at nor intended for use by any investors or prospective investors, and may not under any circumstances be relied upon when making a decision to invest in any fund managed by a16z. (An offering to invest in an a16z fund will be made only by the private placement memorandum, subscription agreement, and other relevant documentation of any such fund which should be read in their entirety.) Past performance is not indicative of future results.

Charts and graphs provided within are for informational purposes solely and should not be relied upon when making any investment decision. Content in this newsletter speaks only as of the date indicated. Any projections, estimates, forecasts, targets, prospects and/or opinions expressed in these materials are subject to change without notice and may differ or be contrary to opinions expressed by others. Please see a16z.com/disclosures for additional important details.

Guillermo Rauch is the founder and CEO of the web development platform Vercel and the creator of Next.js, one of the most widely used frameworks on the internet.

In a fireside chat with a16z Investment Partner Gabriel Vasquez, Rauch explained how open source can accelerate product-market fit and why ruthless focus matters more than ever in the age of AI.

Watch the full fireside below, or scroll down for our top five takeaways from the conversation.

1. Open Source Is a Speedrun to Product Market Fit

Rauch’s framework for open source is to treat it as a filter. The two hardest problems for any startup are getting people to know you exist and building the right thing. Open source, in his view, stress-tests both at once.

“I’ve always thought of open source as a speedrun to product-market fit, because if people don’t use it when it’s free, when it’s easy to consume, when the code is available, then you probably should be working on something else.”

He acknowledged the obvious downside: openness makes replication easier, especially in the age of agents. But Rauch argued that the best open source projects extend into broader platforms, and success surfaces new problems to solve. Next.js itself is only a sliver of the cloud problem enterprises actually face.

“What stops entrepreneurs in their tracks is that they worry too much about what’s going to happen in the future. In reality, they don’t even have product-market fit yet.”

2. Unbounded Vision, Ruthless Focus

Asked about the most important focus decision in Vercel’s early days, Rauch described a tension he calls the “bicameral mind.” You need a bold, boundless long-term vision. But on any given Tuesday with three people in the room, that same ambition will destroy you if you let it dictate what you build.

“When you’re getting started and you’re three people, if all you do every day is unbounded ambition and building two hundred million different features, then you’ve fucked up.”

Early Vercel tried to make everything deployable: every language, every runtime, every framework, even databases. Then Rauch forced the question: where are we being truly excellent? The answer was the front-end layer, a new kind of managed service that didn’t exist yet. The result was the difference between building something no one would pay for and building something worth hundreds of millions.

“If I had continued doing everything, I would have made a company that made zero dollars. Literally zero dollars. Discerning buyers want the best of each class of problem. They don’t settle for the second-best solution.”

3. Choosing What to Build Matters Most

In an era where AI makes everything buildable, the temptation is to build everything. But that’s exactly backward. When every problem becomes shallow with enough tokens, choosing which problems deserve your attention becomes the real competitive edge.

“A bunch of you are probably already over-building massively because you notice that you can just prompt it and it’ll do it. But the discernment of what problems are worth solving could be one of your biggest differentiators.”

He illustrated the point with a contrast from inside Vercel. A good use of AI: having an agent work overnight on a JavaScript optimization that made the platform twenty to forty percent faster for customers. A bad use: rewriting your internal HR tools. The CEO’s job, Rauch argued, is increasingly about helping the company decide what’s worth investing in when everything is possible.

4. Hire for Proof of Work and How People Package Their Ideas

On talent, Rauch’s advice was to look for people on the rise rather than people who’ve already arrived. Find the ones shipping high-quality work, especially with AI tools, and pay attention to something most hiring managers ignore: how candidates communicate what they’ve built.

“Sometimes the reason I reach out to people is not just what they built, but how they communicate it.”

He told the story of sliding into a developer’s DMs after seeing their novel approach to a well-known UI problem, while also finding a new way to package and explain a contribution. Rauch extended this into a broader product philosophy, comparing it to Apple’s unboxing experience: the website, the store, the feeling of lifting the lid. Every layer of the experience has been thought through.

“I sometimes see slop landing pages from startups. It’s a recording of the entire desktop of the entrepreneur, and it’s just so busy. I see his dock with two hundred applications, his entire browsing history, two hundred plugins. Delete all the things that are not your thing, because they’re an excuse for people to get distracted.”

5. Choosing What to Dismiss Is a Competitive Advantage

Rauch closed with a point about conviction. In a world where every new tool and framework generates immediate hype, the ability to say “no” is underrated. His approach is to never outsource judgment. He downloads products, signs up, uses them firsthand. If he can’t deeply understand something himself, he doesn’t build conviction around it.

“Silicon Valley has this sharp edge of people just get so f***ing excited about everything. And some of those things are worth dismissing. Choosing what you dismiss can also be a competitive advantage.”

The two-phase process he described: experiment broadly, then set a high bar for what you actually bring to market. When you do find something that clears that bar, go all in. Post it everywhere, email it, present it. But don’t confuse the excitement of experimentation with the conviction required to ship.

“If I don’t fully understand it myself, it’s very hard for me to actually build conviction.”

Thanks to Guillermo Rauch for sharing his insights with our founders. And for more weekly dives into the world of early stage startups, subscribe below.

You are receiving this newsletter since you opted in earlier; if you would like to opt out of future newsletters, you can unsubscribe immediately.

This newsletter is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. You should consult your own advisers as to those matters. This newsletter may link to other websites and certain information contained herein has been obtained from third-party sources. While taken from sources believed to be reliable, a16z has not independently verified such information and makes no representations about the enduring accuracy of the information or its appropriateness for a given situation.

References to any companies, securities, or digital assets are for illustrative purposes only and do not constitute an investment recommendation or offer to provide investment advisory services. Any references to companies are for illustrative purposes only; please see a16z.com/investments. Furthermore, this content is not directed at nor intended for use by any investors or prospective investors, and may not under any circumstances be relied upon when making a decision to invest in any fund managed by a16z. (An offering to invest in an a16z fund will be made only by the private placement memorandum, subscription agreement, and other relevant documentation of any such fund which should be read in their entirety.) Past performance is not indicative of future results.

Charts and graphs provided within are for informational purposes solely and should not be relied upon when making any investment decision. Content in this newsletter speaks only as of the date indicated. Any projections, estimates, forecasts, targets, prospects and/or opinions expressed in these materials are subject to change without notice and may differ or be contrary to opinions expressed by others. Please see a16z.com/disclosures for additional important details.

What will happen to spreadsheets in the age of AI?

Already, a transition is underway. The big AI labs are building their own integrations for agents in Excel and Google sheets. Startups are getting in on the action too, with teams like Fundamental Research Labs (SR002) earning traction by reimagining the spreadsheet experience to be AI native.

Last week, a16z speedrun General Partner Andrew Chen kicked a hornet’s nest on X with a post arguing that “anything that is currently modeled as a spreadsheet is better modeled in code.”

Here’s the full post, to save you a clickthrough:

AI code gen means that anything that is currently modeled as a spreadsheet is better modeled in code. You get all the advantages of software—libraries, open source, AI, all the complexity and expressiveness.

Think about what spreadsheets actually are: they’re business logic that’s trapped in a grid. Pricing models, financial forecasts, inventory trackers, marketing attribution—these are all fundamentally *programs* that we’ve been writing in the worst possible IDE. No version control, no testing, no modularity. Just a fragile web of cell references that breaks when someone inserts a row.

The only reason spreadsheets won is that the barrier to writing real software was too high. A finance analyst could learn =VLOOKUP in an afternoon but couldn’t learn Python in a month. AI code gen flips that equation completely. Now the same analyst describes what they want in plain English, and gets a real application—with a database, a UI, error handling, the works. The marginal effort to go from “spreadsheet” to “software” just collapsed to near zero.

This is a massive unlock. There are ~1 billion spreadsheet users worldwide. Most of them are building janky software without realizing it. When even 10% of those use cases migrate to actual code, you get an explosion of new micro-applications that look nothing like traditional software. Internal tools that used to live in a shared Google Sheet now become real products. The “shadow IT” spreadsheet that runs half the company’s operations finally gets proper infrastructure.

The interesting second-order effect: the spreadsheet was the great equalizer that let non-technical people build things. AI code gen is the *next* great equalizer, but the ceiling is 100x higher. We’re about to see what happens when a billion knowledge workers can build real software.

The post racked up over a million views and hundreds of replies, with not everyone in agreement.

Richard Pham argued that much of the value of spreadsheets is in the grid-based visualization itself:

Allie Harris came at this question from a different angle:

Tom Robbins was skeptical as well, pointing to the continued ubiquity of PDF files:

This was a a comparison Andrew was happy to run with:

The question is whether spreadsheets will follow the same trajectory—still around, but no longer the default way a billion people interact with data and business logic.

An interesting framing in the thread came from Dan Hockenmaier, who pointed out that there are really two kinds of spreadsheet use. The “mini software” kind—dashboards, trackers, attribution models—is almost certainly getting replaced. But the other kind where you develop a financial model you build to hone your own understanding of a business is stickier.

One top reply came from Robert L. Peters, who offered a full-throated defense of the spreadsheet:

Would bet my net worth with 100x leverage that front office finance jobs will still use spreadsheets 10 years from now

Can you run an LBO model with python, audit each cell (F2), make micro adjustments to formulas with instant feedback, toggling an assumption back and forth to see how it impacts a sensitivity table that is 1000 calculations later in the chain? And do this with someone who just got out of college a couple months ago?

The act of making the spreadsheet in many cases forces the user to think about assumptions, and reason about the drivers. You may not always have it fully formed in your head in advance as a prompt until you see the data, create an operating build, etc.

If an MD draws on their iPad “make a box here, increase spacing in these three areas, change the calculation for this one year of EBITDA to xyz, and make an italics EBITDAR line underneath, break out product lines in revenue build, shift to monthly, etc” they can give to an analyst and can get back exactly what they want to see in an hour. They don’t need to wait 12 months for a SaaS platform to maybe add the feature. Or prompt an LLM that may asymptote on what you want but isn’t perfect.

There are also so many edge cases for bad data from private companies where you really need to manually look at the data points to understand the gaps. Python doesn’t allow you to do that and prompting doesn’t provide a visual surface.

I’m sure you will be able to prompt a lot of this stuff but for many use cases the form factor will continue to be a spreadsheet - the analyst will be able to make tweaks to the spreadsheet output the LLM makes, check the logic easily, make edits where it’s faster to make it the way you want vs type out prompts, etc

In front office finance jobs (maybe other than VC which is less precise with modeling), one single calculation error can dramatically change the answer and cost you $1 million or $1 billion. 95% right is 0% useful. Python and prompting do not allow for full verification of the calcs and data through to the primary sources.

Tech ppl perennially have a fundamentally flawed mental model of Excel (“why not use Python????”) because they have never had exposure to how it’s used in the real world, and it’s why so many companies with the business model “move your OUTDATED spreadsheets to my MODERN B2B SaaS in your browser!” that for the past decade have spammed PE firm inboxes have crashed and burned

Spreadsheets are a better form factor than python for business users and LLMs won’t kill spreadsheets

Peters’ reply gets at something the original take arguably doesn’t address: The act of building the model is how you develop conviction about the inputs. You can’t just skip to the output.

Chen pushed back:

What you’re talking about is the “IDE” user experience of spreadsheets -- being able to inspect the logic, checking out values/cells/etc, debugging, etc. I both agree that you’ll need to do that BUT also that this is all possible, and frankly, better, in software as well

In software you also get unit/integration tests, version control, coding harnesses, AI everything, and much more. You could even ask the LLM to describe the code in a grid if you want to try to be quasi-backwards compatible.

Chen is saying those workflows migrate to a better substrate.

But you can’t win ‘em all. Joel Grus came off the top rope with this zinger:

So, after a day of fighting in the reply guy trenches, Chen posted a followup (full text below):

Reading the replies -- a lotta folks hate this prediction!

A lot of folks can’t imagine programming the logic/variables/inputs without the spreadsheet grid paradigm

My primary counterpoint:

• Much complaining is from people trained on keyboard shortcuts in Windows Excel on Thinkpads during their glorious banking days, swearing that they’ll never switch to anything else. Late adopter normie finance bros. Soon to be disrupted

My actual counterpoints:

• Programming itself has changed its UX many many times. Punchcards, typing into files, IDEs, and now LLM coding harnesses. Spreadsheets are not the only way to encode business logic -- there are better ways, while gaining all the power of software

• The grid UX might remain in some form, but might be more of a display. Just as you code in Codex/Claude but then still pull up a webpage. Or maybe you’ll have a grid as a DB but then build apps on top, but still want a querying UI for the data

• LLMs will make going between logic in code and logic in spreadsheets interchangeable. So maybe you’ll edit in a grid but then hit “deploy” and it’ll build a webapp in the cloud. And just as we have VLOOKUP() they’ll be LLM() that can encode AI logic

• Anyone who works with software knows its infinitely better and more expressive and more powerful. AI code gen is a blessing for all the non-technical excel wizards who can now take their work to the next level

The history of computing really is a story of interfaces evolving beyond what the previous generation thought was possible. Punchcards felt essential until they didn’t. Command lines felt essential until GUIs arrived.

The spreadsheet grid might be next.

What do you think about the spreadsheets debate? Let us know in the comments. And for more weekly dives into the world of early stage startups, subscribe below.

You are receiving this newsletter since you opted in earlier; if you would like to opt out of future newsletters, you can unsubscribe immediately.

This newsletter is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. You should consult your own advisers as to those matters. This newsletter may link to other websites and certain information contained herein has been obtained from third-party sources. While taken from sources believed to be reliable, a16z has not independently verified such information and makes no representations about the enduring accuracy of the information or its appropriateness for a given situation.

References to any companies, securities, or digital assets are for illustrative purposes only and do not constitute an investment recommendation or offer to provide investment advisory services. Any references to companies are for illustrative purposes only; please see a16z.com/investments. Furthermore, this content is not directed at nor intended for use by any investors or prospective investors, and may not under any circumstances be relied upon when making a decision to invest in any fund managed by a16z. (An offering to invest in an a16z fund will be made only by the private placement memorandum, subscription agreement, and other relevant documentation of any such fund which should be read in their entirety.) Past performance is not indicative of future results.

Charts and graphs provided within are for informational purposes solely and should not be relied upon when making any investment decision. Content in this newsletter speaks only as of the date indicated. Any projections, estimates, forecasts, targets, prospects and/or opinions expressed in these materials are subject to change without notice and may differ or be contrary to opinions expressed by others. Please see a16z.com/disclosures for additional important details.

Ben Horowitz has been advising founders for decades.

In a recent fireside chat with a16z speedrun General Partner Jonathan Lai, Ben made the case that the fundamentals haven’t changed nearly as much as people think. Strategy is still about articulating a clear “why.” Product management is still about shipping the right product at the right time. And the best fundraising pitch is still the one you actually believe.

What has changed is the landscape around those fundamentals. And there are massive new opportunities hiding in plain sight, if you know where to look.

Watch the talk in full below, or read on for five takeaways that stood out to us.

1. Your Story Is Your Strategy. Write It Down.

Horowitz opened with a point that sounds simple but that most founders get wrong: your company’s story and its strategy are the same thing. Not adjacent. Not related. The same. And if you aren’t constantly rewriting that story as you learn, your strategy is drifting without anyone noticing.

“The story of the company is also the strategy of the company. Nobody’s got some strategy in their back pocket that’s entirely secret and then a story that’s different.”

He pushed founders to write it in long form, because that forces the most discipline. The story answers the “why”: Why does this company exist? Why should someone join? Why should someone invest? If people know the why, Horowitz argued, you don’t even have to tell them the what.

“The problem that founders have is it doesn’t feel like work. ‘What are you doing today?’ ‘Oh, I’m working on my story.’ That doesn’t sound like work. But it’s probably one of the most important parts of the job.”

2. In the AI Era, Hire for Creativity and Relationships

Asked what traits founders should prioritize when hiring, Horowitz pointed to two that Silicon Valley has historically undervalued: creativity and relationship-building. AI already handles the grind-it-out tasks. What it can’t replicate is someone who walks in with original ideas or who can build and maintain high-fidelity relationships.

“If you don’t have instincts around those things, I don’t know that all the AI in the world can help you. Whereas the grind-them-out tasks, AI is already really good at.”

He illustrated this with a story from his own firm. They had built a legendary marketing organization, but it was rooted in 2009-era traditional media. It wasn’t until they brought in people who were genuinely creative about new media that the firm could break through on that front. Original thinking, Horowitz noted, is rarer than people assume.

3. “Right Product, Right Time” Is Still the Only Job

Horowitz’s essay Good Product Manager, Bad Product Manager has become required reading in product circles. But the origin story is more blunt than most people realize. He wrote it because he was furious at seven PMs who were doing everything except the one thing he needed from them.

“I was so f***ing mad at them because I was like, ‘You people are doing everything but your job.’ You’re writing these requirements, you’re running around, pitching customers this and that. It’s a lot of work. But your job is: right product, right time. And if you don’t give me the right product at the right time, I don’t give a f*** what you do.”

When Lai asked whether the AI landscape changes the PM role, Horowitz was characteristically direct. The landscape doesn’t change the job. It’s still about “right product, right time.”

“You sound like my f***ing product managers. ‘Oh, now the landscape is different. I won’t write a PRD, I’ll write a prompt.’ Okay, great. Is it going to get you the right product, right time? If not, it doesn’t matter… And if you can’t do that, then Opus 4.6 can do all those tasks. No problem.”

---

4. Build Where There Are Shortages

Asked about the most exciting opportunities for founders, Horowitz pointed to areas where there are shortages. If there’s unlimited demand for AI tokens, the interesting question becomes: what supply-side bottlenecks can you solve?

“We’ve got an electricity shortage, chip shortage, token shortage. We’re going to have a cooling shortage. There’s all kinds of levers that you can pull to alleviate some of those shortages, and those will be valuable.”

There are examples Ben pointed to, like a16z’s decision to back Heron Power, a company building power transformers, because the shortage is so severe that it’s a bottleneck for new power plant construction. Horowitz also flagged a second category: long-standing problems of humanity, like cancer, that could become solvable thanks to new technology.

5. The Best Fundraising Pitch Convinces You First

When the conversation turned to fundraising, Horowitz’s advice cut against the instinct most founders have when walking into a pitch meeting: trying to figure out what the investor wants to hear. Instead, you should be able to convince yourself first:

“Being able to articulate why you’re building this company in a way that convinces even you that you should re-join your company is really the thing. If you can convince yourself completely that this is the greatest freaking idea in the world, then that’s the most compelling thing… The mistake people make in fundraising is they go, ‘Well, what does Ben want here? Does he want to see a graph like this? Does he want to know this about market size?’ That’s very hard to figure out, and you usually get it wrong. But you can know: how would I convince myself to join this company, or invest in this company? That always works the best.”

The reason is practical, not philosophical. A pitch built on what you believe is a pitch you can’t get talked out of. The worst outcome in a fundraising meeting is someone poking a hole in your narrative and you folding, because the argument was never yours to begin with.

“It’s kind of like a bad way to start a relationship. ‘I’m going to pretend to be this other person and then you’re going to like me, but then we’re going to get together and you’re going to find out the real me.’ That tends not to work out either.”

Thanks to Ben Horowitz for sharing his insights with our founders. And for more weekly dives into the world of early stage startups, subscribe below.

You are receiving this newsletter since you opted in earlier; if you would like to opt out of future newsletters, you can unsubscribe immediately.

This newsletter is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. You should consult your own advisers as to those matters. This newsletter may link to other websites and certain information contained herein has been obtained from third-party sources. While taken from sources believed to be reliable, a16z has not independently verified such information and makes no representations about the enduring accuracy of the information or its appropriateness for a given situation.

References to any companies, securities, or digital assets are for illustrative purposes only and do not constitute an investment recommendation or offer to provide investment advisory services. Any references to companies are for illustrative purposes only; please see a16z.com/investments. Furthermore, this content is not directed at nor intended for use by any investors or prospective investors, and may not under any circumstances be relied upon when making a decision to invest in any fund managed by a16z. (An offering to invest in an a16z fund will be made only by the private placement memorandum, subscription agreement, and other relevant documentation of any such fund which should be read in their entirety.) Past performance is not indicative of future results.

Charts and graphs provided within are for informational purposes solely and should not be relied upon when making any investment decision. Content in this newsletter speaks only as of the date indicated. Any projections, estimates, forecasts, targets, prospects and/or opinions expressed in these materials are subject to change without notice and may differ or be contrary to opinions expressed by others. Please see a16z.com/disclosures for additional important details.

YOU’RE INVITED: Want to host a Tech Week event in NYC or Boston this summer?

The Tech Week team is hosting office hours next week to walk you through how to get listed, promote your event, and make it a great one. RSVP here.

Most founders think fundraising is about selling investors on their vision. I believe it’s not. It’s about making it easy for an investor to say yes.

Here’s some inside baseball: unless you are pitching a solo GP, it’s often not enough for the investor you’re talking to to fall in love with the opportunity. They have to convince the rest of their team to love it too.

This requires writing an internal investment committee memo that translates your story into a case for why the fund should wire you millions of dollars. And they’re doing this for dozens of deals simultaneously, while fielding new pitches, managing portfolio companies, and trying to leave the office before 9pm.

So when it comes down to two promising companies and one evening to write an IC memo, which deal moves forward? The one where the partner has a five-page written document in the founder’s own words? Or the one where they have to reconstruct the narrative from a six-slide deck and some scribbled notes from the week before?

I’ve observed this dynamic play out dozens of times. The decision to bring a company into an investment committee meeting sometimes has less to do with level of conviction and more to do with whether the investor has time to do proper due diligence to write a complete memo. That might sound cynical but it’s reality in a world governed by tradeoffs.

I’ve personally had teams come in where, honestly, I was lukewarm based on the deck. Maybe they were deeply technical and not natural communicators. But when I read their memo, I could see the depth of thinking. The level of rigor changed my read on the entire company.

To put it simply, a great memo helps an investor more accurately price your potential.

And beyond the utility for fundraising, it’s a useful exercise for you, too. The discipline of writing in full prose and structuring your thinking on paper forces a level of clarity that high level bullet points on slides simply don’t require.

This is why every founder I work with at speedrun now writes an investment memo. I think you should write them too.

So what does a great memo look like?

What Goes in the Memo

What follows is a template that I share with every founder I work with.

One-Liner

Your company in a sentence. This should be crisp enough that someone can repeat it from memory to a colleague. In the earliest stages saying something like “We are the X for Y” e.g. “We are the Cursor for Sales” is totally fine. As you get deeper into your journey you’ll want to abandon that framing.

Team Overview

This is the section investors flip to first and your most important one, so you might as well put it in the front. Before they read anything about your market or your product, they want to know who’s building this and why they should care.

Include founder backgrounds with enough detail that an investor can quickly assess relevant experience. What notable things have you accomplished to date? What makes you exceptional? What have you gone 0 to 1 on? If you have a social following, mention it. It can eventually help for distribution. Outline the broader team if applicable, and if you have impressive or relevant advisors, include them.

The core question you’re answering is why is this the right team to win in this market?

Side note: you should hyperlink your Linkedin to your name. The first thing investors want to do when they come across a new opportunity is to pop open their profile to see if they have mutual connections and can therefore reference the team. I know that hyperlinking seems like a silly thing to make sure to do, investors do have opposable thumbs and can type into a search bar, but a quality memo is built by a hundred tiny touches.

Problem and Market Overview

What is the problem, and how big is it? Keep this concrete. Avoid hand-wavy TAM calculations as these are always bullshit. If you can, frame the problem through tangible examples. One memo I got recently did this right by starting with, “sales people at a distributor spend 50% of their time slicing through the messy inbox problem and manually inputting data into a legacy system to generate a quote.” Another option is analogies from spaces with similar root problems (“we’re Tennr for Distributors”) an investor can relate to. This is much better than dubious TAM figures. The best problem statements make the reader think “of course someone should solve this.”

Product Overview

What does the product actually do, and what is your clear wedge into the market you’re attacking? This section is also where the “why now” belongs. What has changed, whether in technology, regulation, behavior, or market structure, that makes this the moment to build a hundred-billion dollar company? Any good idea has likely been tried before, so identifying the current tailwinds is essential.

GTM Strategy

Who is your ideal customer, and how are you getting in front of them? If you have any unique distribution advantages, unfair access to customers, community-driven growth, partnerships, whatever it is, this is where you make that case. Investors want to know you’ve thought about how this thing actually gets sold, not just built.

Business Model

How will you make money? If it’s going to evolve over time as you move upmarket or add product tiers, describe that evolution. Keep it simple but be specific.

Even if you’re early and haven’t fully validated your pricing model with customers yet, demonstrating that you have a working theory here substantiates that you’re building a venture scaled business and not just a cool product.

Traction

This section will vary enormously depending on your stage. At pre-seed, you may only have design partners or letters of intent. At seed, you might have real revenue. At Series A, you should have retention and expansion data.

A few things to include if you have them: an overview of design partners or marquee logos, what they’re paying now and what they could be worth at scale, and whether contracts represent actual billed ARR or contractual commitments not yet billed.

A pet peeve of mine, that’s worth flagging: Do not refer to non-recurring revenue as Annual Recurring Revenue. If your revenue is predictable but not contractually recurring, call it Annualized Run-Rate Revenue and spell that out. If investors think you’re being deceptive with this label, it will break trust.

If you have the data, include monthly revenue charts and monthly customer counts to show acquisition growth and momentum (note: if you don’t show a chart, investors may assume that the growth isn’t great). The other important charts to include are logo retention by cohort and net dollar retention. The a16z blog has excellent breakdowns of the key metrics for both B2B and consumer/prosumer businesses. Include those metrics. Investors know them, and showing you know them too signals sophistication.

If you’re a Series A/B company you may be able to drop in a chart that is going up and to the right to signal that “it’s working” and that you have PMF. Before then, traction can be more about signals (“we’re in a late stage paid pilot with Enterprise Customer A with the opportunity to expand across the entire org”) than raw numbers. Being able to properly contextualize your early traction becomes one of the most important ways that memos trump decks. Use that to your advantage.

Competitive Landscape

Who else is in this market, and why are you going to win? What’s your unique advantage? Investors don’t expect you to have zero competition because great markets attract many great founders. They expect you to have done your research on the competition and have a credible theory for why you’re differentiated.

Vision

What’s the five-year picture? How does the market evolve, and how does your company evolve with it?

Once you’ve penetrated the market with your thin wedge, what is your plan to expand the product surface area and dominate the category? This section is your line of defense when an investor believes your initial product has a limited TAM or is more of a feature than a full product. You should identify how owning your wedge gives you the right to win the category. So if you were building software that will eventually replace ERP (Enterprise Resource Planning) systems you could defend it with something like, “by building the ‘system of action’ with agents above an ERP we can eventually build and replace the ERP.”

This is your chance to show the investor the larger arc of your vision: the insight that turns a useful product into a large and important company.

Next 12 Month Plan and Use of Proceeds

Lay out what you plan to accomplish with the capital you’re raising. Where will it go? What milestones will it unlock?

I would offer one piece of counterintuitive advice: do not put the specific amount you plan to raise in the memo. That should be a live discussion. Writing it down anchors the conversation in a way that can work against you.

When a Memo Matters Most (and When It Doesn’t)

Not every company benefits equally from a memo. I believe the highest-leverage scenarios are:

Contrarian or obscure markets. If you’re building vertical AI for lumber distributors or rail operators or food distribution, the investor probably doesn’t already know your market. They need to be educated on why this is bigger or more interesting than it looks. A memo lets you do that in a way slides can’t.

Technical teams who aren’t natural communicators. Some of the best founders I work with are deeply technical. In a quick intro call, they may not shine. But when they can lay out their thinking in written form, you can see the rigor. The memo becomes the great equalizer between business and technical founders.

Post-meeting follow-ups where the investor is on the fence. If someone is deciding whether to take a second meeting or bring you into their process, having a written document that answers the obvious follow-up questions can tip the balance.

Where a memo matters less: if you’re building in a well-known, fast-moving market like AI Video editing, every informed investor already knows the space. A five-page market breakdown is going to be out of date in three months. In those cases, the memo should lean heavily on team and traction, not market education. Don’t write pages about a market the investor already understands.

The Deck and the Memo Are Not Mutually Exclusive

This isn’t an either/or. You should have both, and they serve different purposes at different moments in the fundraising process.

The teaser deck is your ticket to the meeting. It gets shared before the first call. Its job is to answer two questions for the investor at a thumbnail level: Is this an interesting team? And is this a market I care about? That’s it. It can be five or six slides and skimmable. It should not try to do more than this.

The memo is what you share after the initial meeting. Its job is to capture everything the investor might have missed, provide depth on the market and the strategy, serve as an FAQ, and demonstrate the quality of your thinking. The deck is the teaser. The memo is the substance. And now that tools like Gamma exist, you can actually write the memo first and generate the teaser deck from it. Write the substance, then extract the thumbnail. That’s a better workflow than the other way around.

The goal isn’t to be exhaustive with your materials. It’s to answer the critical questions and get to the next meeting.

A Few More Tactical Notes

On length: One important caution. Particularly at the pre-seed stage, don’t say so much that you give the investor enough rope to hang you. The goal is to answer the critical questions and get to the next meeting. At pre-seed, aim for three pages and make it mostly about team and market opportunity. At seed, five is a good ceiling. Even at Series A, anything beyond eight or ten pages is probably too long. If it feels too long, it probably is. Say just enough. Not more.

When your memo is too long investors may throw it into ChatGPT and ask for a summary. I’ve done this. Many investors I know have done this. So you might as well write something tight enough that it doesn’t need to be compressed by a language model to be useful.

More excitingly, AI is to change what an investment memo can be: One founder recently sent me a long FAQ document along with a system prompt and told me to put both into Claude. The system prompt would generate a memo from the FAQ, and then the investor could ask follow-up questions based on all the source material. I’m not sure I’d recommend this as your primary approach, but it was creative, and it points to a real truth: investors can use AI to process your materials whether you design for that or not.

On writing the memo even if you don’t “need” one: Even if you are one of the select few founders who can raise without written materials, the act of writing the memo is still valuable. It forces you to structure your thinking, identify the weak points in your narrative, and articulate things you may have only ever talked about out loud. Many founders tell me the writing process changed how they thought about their own company. Further, even if you can raise on just your name, if your investors do not deeply understand your vision and direction, it can be harder for them to actually help you build.

The Case for Substance

Long-form is back. Investors want substance. The best founders I work with understand that a well-written document in their own voice is one of the highest-leverage things they can produce during a fundraise. It can be the difference between an investor who’s interested and an investor who falls in love.

Write the memo. Make it easy for people to say yes.

Have questions about investment memos? Reply and let us know. And for more weekly dives into the world of early stage startups, subscribe below.

You are receiving this newsletter since you opted in earlier; if you would like to opt out of future newsletters, you can unsubscribe immediately.

This newsletter is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. You should consult your own advisers as to those matters. This newsletter may link to other websites and certain information contained herein has been obtained from third-party sources. While taken from sources believed to be reliable, a16z has not independently verified such information and makes no representations about the enduring accuracy of the information or its appropriateness for a given situation.

References to any companies, securities, or digital assets are for illustrative purposes only and do not constitute an investment recommendation or offer to provide investment advisory services. Any references to companies are for illustrative purposes only; please see a16z.com/investments. Furthermore, this content is not directed at nor intended for use by any investors or prospective investors, and may not under any circumstances be relied upon when making a decision to invest in any fund managed by a16z. (An offering to invest in an a16z fund will be made only by the private placement memorandum, subscription agreement, and other relevant documentation of any such fund which should be read in their entirety.) Past performance is not indicative of future results.

Charts and graphs provided within are for informational purposes solely and should not be relied upon when making any investment decision. Content in this newsletter speaks only as of the date indicated. Any projections, estimates, forecasts, targets, prospects and/or opinions expressed in these materials are subject to change without notice and may differ or be contrary to opinions expressed by others. Please see a16z.com/disclosures for additional important details.

Tomorrow is the final day to apply for the first-ever cohort of a16z speedrun Alpha, a selective fellowship for exceptional students and recent-grad engineers who want to build startups, either by joining a breakout portfolio company at the ground floor or starting one themselves.

Applicants on Alpha’s Founder Track get a $20k grant and access to up to $250k in follow-up capital, plus priority consideration for a16z speedrun. For those who aren’t yet ready to found, we’ll place you with one of our portfolio companies.

Getting in can change the slope of your career. There’s no reason to wait, so apply today.

In June, the first cohort of Alpha will kick off with a retreat alongside the speedrun team, followed by 8 weeks in person with some of the smartest engineers and operators in the ecosystem. Companies started by Alpha fellows will receive fast-tracked consideration for a16z speedrun.

For those with questions about the program, check out the below Q&A with program co-leads Katia Ameri and Jordan Mazer below.

Q&A

A16Z SPEEDRUN: What led to the creation of Alpha? What need were you seeing?

KATIA AMERI: AI has made it much easier for someone early in their career to actually ship meaningful projects. You don’t need a huge team or a ton of capital to start experimenting. So we were seeing talented people all over building interesting products, sometimes from school, or sometimes from side projects. We realized we wanted a way to meet those people earlier and give them a direct path into startups.

There are two tracks within the fellowship. One is for people who want to join a fast-growing portfolio company and learn by building alongside a founding team. The other is for people who know they want to start something but are still at the earliest idea stage. For them, we give them the capital and infrastructure they need to actually start building.

JORDAN MAZER: There’s a war raging in every channel: poasters on X talking about the next single employee startup that will reach a $1B valuation, Dario going on every broadcast available to postulate about the total collapse of the white collar new grad job market, Citadel recently releasing a report showing that new company creation has gone into hyperdrive.

Common across nearly all of the mediums and personalities is an earnest belief that tectonic upheaval is happening to us in real time. They all agree tools are more capable than ever before, and builders are accumulating leverage at an unprecedented rate. What they seem to disagree on most is when layoffs will occur, and how big the layoffs will be.

Here’s what I see every single day: more and more exceptional students and recent grads struggling to find work they’re excited about. The question is: what happens when exceptional students matriculate into a market that isn’t sure what to do with them? And, more specifically, what happens if those exceptional people happen to be J.A.R.V.I.S.-infused-superhumans who are in no way laden with a) all of the debt of being a big existing company, or b) all the habits of building software in a BC (“before Claude”) world?

Our belief is that many of those young matriculants (or cracked dropouts) are going to do incredible things. Build incredible things. Change the world and markets. And, to be perfectly clear, we’re not just betting with our words.

You’ve announced that the program includes a kickoff retreat, dinners, and AMAs, but what does a random Tuesday in week four actually look like for a Talent Track fellow versus a Founder Track fellow?

KATIA AMERI: For someone on the Talent Track, a random day is mostly their full-time job. They’re embedded at their company, working alongside the team, and the fellowship programming happens around that, usually in the evenings (like cohort dinners or AMAs).

For someone on the Founder Track, the day is focused on building their own idea. We’ll have a shared workspace where fellows can work alongside each other, and there will be structured touchpoints like office hours and cohort dinners. For both tracks, we’re also planning behind-the-scenes visits to portfolio companies at different stages so folks can see how startups operate up close.

The Alpha website says “technical background and experience shipping real work.” But between two candidates with similar resumes, what actually tips the scale? Are you pattern-matching to something specific, or is it more of a “you know it when you see it” thing?

JORDAN MAZER: The strongest candidates will be honest, both with themselves and with us, about what they are trying to achieve. Being honest is harder than it sounds. Because having an honest perspective about what you want requires introspection (very rare) while also understanding the options laid out in front of you (hard for someone at this stage of life!).

Most candidates try to be everything for everyone. They say they’re open to any stage. They say they’re open to any industry. They say they’re open to any problem. Sometimes it’s because they honestly don’t have an informed preference (which doesn’t mean they are open to anything, it just means they don’t know what they want). Often it’s because they aren’t sure what the “best answer” is, irrespective of their actual desires, so they are trying to say the thing that will “keep them in the running.” By trying to be everything to everyone, candidates become totally undifferentiated. It turns otherwise promising applications into forgettable fodder for the rejections folder.

The most interesting prospects will have clarity about their preferences. They will be opinionated (even if they’re wrong!). They’ll tell me they love [X] and that they absolutely abhor [Y], without fearing the risk of affecting my opinion of their fitness for the program. They are honest because, to them, the program is a means to an end: the end of working on what they want to work on. For them, the program itself is only important insofar as it supports their goals and intent.

Some strong candidates will want to work on rockets. Others on high-frequency trading tech. A handful will find the idea of working on AI-driven weapons to be morally objectionable, while some other prospect will tell me it’s a moral imperative. Many will want to found and others will want to join. Common among all of the “strong prospects” we select will be the core capacity to be honest with themselves and with others, and to have conviction in their path.

KATIA AMERI: I’d say what really tips the scale is initiative. We look closely at what someone has actually built. Did you go deep on something because you were curious, and when no one asked you to? We care a lot about demonstrated intellectual curiosity and a bias toward action.

How does the disbursement work between the initial $20K and the rest?

KATIA AMERI: On the Founder Track, we’re often backing people at the individual level, before there’s a company formed. It starts with a $20K grant that we give directly to the fellow upfront. Once they’ve formed an entity, refined the idea, and there’s something more concrete, they become eligible for up to $250K in investment.

Jordan, you’ve been interviewing hundreds of Alpha candidates already. What’s standing out to you about the people who’ve applied so far?

JORDAN MAZER: The range. One of the first founder candidates I spoke with has several planets named after him (from the work he did identifying said planets at NASA… while in high school). Another built a non profit that donated shoes to tens of thousands of impoverished people. She was 13 when she started building it. One was the youngest to ever intern at Lockheed. Another was a challenger-ranked Yasuo main (NA, tho 😭).

Then I get some who ask for extensions on challenges, or who didn’t even read the application and are surprised the program isn’t for internship opportunities or who “just want to found for the summer.”

What about co-founder matching? The Alpha site says you can apply pre-team. In practice, do you expect most Founder Track fellows to find co-founders within the cohort?

KATIA AMERI: For the Founder Track, some people will apply solo, some people will already know who they want to build with. We don’t require a pre-formed team. That said, we’re intentionally creating an environment where the fellows will spend a lot of time together, so we expect that some co-founder relationships will form organically as a result.

What does it mean when we say Founder Track fellows get “priority consideration” for speedrun?

KATIA AMERI: The goal of Alpha is to set you up to be in a strong position for speedrun, which is our flagship program. During the cohort, you’ll have touchpoints with the speedrun team and a clear sense of what we’re looking for. So if, by the end of Alpha, you’ve refined your idea and want to pursue speedrun, you’ll get a guaranteed final-round interview.

Have questions about the Alpha Fellowship? Reply and let us know. And for more weekly dives into the world of early stage startups, subscribe below.

You are receiving this newsletter since you opted in earlier; if you would like to opt out of future newsletters, you can unsubscribe immediately.

This newsletter is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. You should consult your own advisers as to those matters. This newsletter may link to other websites and certain information contained herein has been obtained from third-party sources. While taken from sources believed to be reliable, a16z has not independently verified such information and makes no representations about the enduring accuracy of the information or its appropriateness for a given situation.

References to any companies, securities, or digital assets are for illustrative purposes only and do not constitute an investment recommendation or offer to provide investment advisory services. Any references to companies are for illustrative purposes only; please see a16z.com/investments. Furthermore, this content is not directed at nor intended for use by any investors or prospective investors, and may not under any circumstances be relied upon when making a decision to invest in any fund managed by a16z. (An offering to invest in an a16z fund will be made only by the private placement memorandum, subscription agreement, and other relevant documentation of any such fund which should be read in their entirety.) Past performance is not indicative of future results.

Charts and graphs provided within are for informational purposes solely and should not be relied upon when making any investment decision. Content in this newsletter speaks only as of the date indicated. Any projections, estimates, forecasts, targets, prospects and/or opinions expressed in these materials are subject to change without notice and may differ or be contrary to opinions expressed by others. Please see a16z.com/disclosures for additional important details.

The a16z speedrun team is hiring! We’d love to get your application for:

1. Events & Community Marketing - Run the founder experience for teams accepted into speedrun

2. Product Growth - Help our founders gain traction through modern product-led growth strategies

3. Demand Generation - Help build our investor community

4. Partnerships Manager, Tech Week - Help grow and support our Tech Week partner network

5. Marketing Partner, Alpha - Help us build and grow our exciting new fellowship program for early-career technical talent

You can also see all our openings here. We can’t wait to receive your application.

Now, onto this week’s main story.

The old founder-led sales playbook went something like this:

You manually send DMs on LinkedIn for two hours, hand-write cold emails to everyone you could think of, track everything in a spreadsheet, pray. If you were selling to enterprises, all you had to do was multiply your expected pain by twelve and add a procurement department.

That playbook is (thankfully) kaput. AI-native founders are now selling to banks, hospitals, law firms, and universities with zero dedicated sales hires. The type of sales processes that used to take 18 months can now go much, much faster.

The unlock comes from two capabilities converging:

1. computer use agents are finally good enough that they can work autonomously

2. automated outbound pipelines are cheap and easily accessible.

In 12 months our inboxes are likely to be spam-filled and stuffed with AI slop. For now though, most of the world hasn’t figured out how to do this, so there is a brief, glorious moment where founder-led sales can use AI to accelerate revenue growth.

Here’s how speedrun founders are building the stack.

Your AI SDR Lives in a Browser Tab

Computer use is the capability that changes everything about solo founder sales. These are AI agents that can see your screen, click buttons, fill out forms, and navigate web apps. By freeing yourself from the constraints of APIs and MCP, you can build a janky but serviceable SDR with a minimal amount of effort.

Tools like Claude Cowork, OpenAI Operator, and similar browser-control agents can do most of the things you can do in Chrome. And most prospecting workflows live in browser-based tools like LinkedIn Sales Navigator and CRMs that either don’t have APIs or charge enterprise prices for access. Computer use bypasses all of that.

Shawn Tsao, cofounder and CEO of Snapp (SR006), runs Cowork on a browser tab pointed at Sales Navigator. It reads his ICP filters, clicks through profiles, and sends connection requests on autopilot, maxing out LinkedIn’s 200-per-week limit. Each lead gets added to a Sales Nav list spreadsheet, which then flows into Dripify for automated LinkedIn drip sequences. His own review: “A bit scuffed, but it saves a ton of time.”

How to replicate this today:

Define your ICP in Sales Navigator using title, company size, industry, and geography filters. Open Cowork (or your browser agent of choice) on that Sales Nav tab. Instruct it in plain English to connect with matching profiles and add them to a named lead list. Then pipe that list into a LinkedIn automation tool like Dripify or Expandi for follow-up sequences. Treat the browser agent as a junior SDR who can do anything you can do in a browser. You just tell it what to do.

To be clear: this will almost certainly break or have weird edge cases. But that’s ok! If you’re an early stage founder, perfect processes are reserved for those with product-market fit.

Tsao adds one more tip:

“I also ended up building my own AI Agent that doesn’t require Sales Navigator but uses publicly found information to get cold leads and even writes out the exact email and places it into my Gmail drafts.”

From Lead to Demo, No Humans Required

The second layer moves beyond simple prospecting into full pipeline automation. AI manages sourcing, enrichment, outreach, and response routing end to end. An orchestration stack typically combines tools like Clay, Lemlist, and Attio as the central hub, connecting data sources, AI enrichment, and outbound channels into a single workflow.

Silvia Chen, cofounder and CEO of Bilrost (SR006), built this exact type of system to sell loan processing automation software to commercial and business-purpose real estate lenders. Leads are sourced, enriched and qualified in Clay, synced into Lemlist for personalized outreach, and routed through an AI-driven decision tree. Each response triggers a different path: message viewed, reply received, no response, objection raised. Each generates its own tailored follow-up sequence, and the system runs autonomously until a prospect is ready for a live conversation.

Chen told us that now her “LinkedIn DMs are so flooded I can’t open the app.” When she launched a last-minute, conference-specific campaign ahead of a major industry event, her calendar filled up from landing to takeoff with high-quality, in-person meetings—selling into banks, one of the most conservative and difficult buyer segments.

How to replicate this today:

Start by building your lead list in a tool like Clay or 11x, which can pull from LinkedIn, Crunchbase, and company databases based on your ICP filters. Use Clay’s AI enrichment to research each lead, write personalized first lines, and identify the right entry point at each organization. Route enriched leads into outreach tools like Instantly or Smartlead for email, or Dripify for LinkedIn, with conditional sequences. Set up branching logic so different follow-ups trigger based on opens, replies, and objections. Then insert yourself only when a lead is qualified and ready for a live conversation. (And if this all sounds too complicated, just copy and paste this paragraph into a coding chatbot of your choice, and you can build it in an afternoon.)

The goal is that you should only be doing the part of sales that requires you personally, the demo, the relationship, and the close. Everything upstream of that can run mostly autonomously.

The Trust Layer: What Automation Can Accelerate But Not Replace

There’s a piece of enterprise sales that no automation stack can skip entirely: Every industry has what GalaxySail cofounder Ruming Zhen (SR006) calls “tokens of trust.”

These are specific artifacts buyers need to see before they’ll engage seriously. Hospitals need published research and conference posters. Schools need pilot results. Banks need compliance documentation. Every industry will have some signifiers of security or quality that it is important to have

AI can’t eliminate the need for these artifacts, but it can compress the timeline for producing them from months to days. Multiple speedrun founders described generating SOC 2 readiness documentation and security architecture summaries using AI rather than hiring consultants. Several discovered that simply getting a letter of intent from a provider like Vanta, showing you’re in the process of obtaining certification, was enough to unblock deals. One current speedrun founder got the letter the same morning he reached out, and it moved a stalled enterprise conversation forward immediately.

The bottleneck in enterprise sales isn’t usually the pitch. It is getting the customer to believe in you comically early in your journey. These tokens of trust give buyers permission to say yes. AI compresses that production cycle dramatically. Identify the one or two trust artifacts your buyer needs, then use AI to produce them in days. Think of these as specialized forms of sales enablement!

Other AI GTM Tools SR Founders Are Using

We asked a wide group of founders from SR006 what AI tools and workflows they’re using for GTM and sales.

Here are five more interesting approaches:

“We built a custom GTM dashboard to enrich public data with founders’ LinkedIn data. This is important since the legal industry operates on warm connections.”
—Ke Ma, cofounder and COO of Concorda (SR006)

“We run a multi-model, agentic GTM stack. GPT-4.1 handles structured reasoning and tool use, Claude 3.7 synthesizes long-form thesis shifts, and Gemini 1.5 processes large context windows for portfolio and filing analysis. Tavily + Apify feed real-time capital signals, a lightweight LangGraph agent loop continuously reprioritizes deployment probability, and outbound + pre-call briefs are regenerated dynamically. CRM is just the execution layer. Inference drives pipeline.”
—Mohamed Mohamed, founder and CEO of Smart Bricks (SR006)

“We’ve found that cold-email outbound is becoming an increasingly tough channel (though Instantly is great) and that trying out many different AI tools can be more distracting than helpful. Going deep with a couple tools keeps us focused. Our ‘outward-facing’ stack for lead-sourcing, enrichment, and outbound centers is Exa + Superhuman. Our ‘inward-facing’ stack for note-taking/ops, CRM, and PM is Notion + Slack + OpenAI suite.”
—Andy Baran, cofounder and CEO of a stealth company in SR006

“At Quanto, we’ve put a lot of our founder-led sales meetings notes and our internal team meeting notes into a custom GPT project. The folks on our team that do sales / customer success will query that first with any inbounds from current and prospective customers to help make it sound like me as the “first line of reasoning.” It has been helpful in scaling and trusting the team to interact directly with clients.”
—Anderson Petergeorge, cofounder and business lead of Quanto (SR006)

“We manage a 5-agent AI sales org. They run async: plugged into our sales stack, sourcing leads, researching prospects, qualifying fit, and writing custom outreach for each. We steer the whole team over iMessage.”
—Stefano Delmanto, cofounder of Mercury (SR006)

The minimum viable sales team

Founder-led sales used to mean the founder does everything manually. Now it means the founder orchestrates agents that do everything. Founders in speedrun are now running sophisticated GTM outreach programs with 1/10 of the resources required five years ago.

The new stack is a browser agent for prospecting, AI tooling like 11x or Clay for enrichment, automated sequencing for outreach just using an email agent, and AI for trust artifacts.

In the earliest stage, no one’s title is “sales,” so why not offload more of that work to AI?

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