The real sales metric might be time-to-trust: the moment a customer stops checking your work.

Because every company can point to a failed AI pilot or a tool that promised the world and never integrated. And if there is even a chance a buyer thinks they can vibecode their way to a solution over a weekend, you’re done. Proving ROI and short time-to-value are necessary but not sufficient.

The question now isn’t “Does your product work?” It’s “Do I trust you enough to bet my operation on this?”

How fast you can get there determines whether you close or die in pilot purgatory.

Find the Shoulder

So how do you know when a customer trusts the product?

Prior to going full time with Garuda, I was an early employee at Legion, where we built an AI-powered workforce scheduling platform for hourly workers (mind you, this was in 2019, before today’s AI wave). When we launched with a new customer, we could watch the same pattern play out every time.

Store managers would receive the AI-generated schedule and tweak it. Swap a shift here, adjust a pairing there, override a timing they didn’t love. The model would quietly learn from every edit and incorporate their preferences into the following week’s schedule. The next week would come around, more edits, and the cycle continued.

And then at some point the edits fell off a cliff. Every time.

This is what I called the trust shoulder. The point where the manager stopped overriding the AI and started relying on it.

Or, more broadly, the moment where the behavior shifts from checking your work to trusting it. And then spending less time in the product.

In the agentic era, trust can actually mean customers using your tool less, not more.

If your AI is handling workflows autonomously, the signal isn’t DAUs or session length. The signal is they stopped logging in to supervise. The old SaaS playbook optimized for usage and engagement. The new one needs to optimize for confident delegation.

Pack Your Suitcase

Many companies solve this by showing up.

One of our Garuda portfolio company saw a 4-5x increase in ACV once they started placing engineers on-site with customers, compared to quarters where they relied on remote sales and CS-assisted demos (and in one case went from $300K to $1M!)

Another built their version of the Iron Man suitcase: travel on-site, spend a week in the prospect’s building, show the product working on their data, and at the end of the week there’s either ROI or there isn’t. No six-month pilot.

One week, go/no-go. Because it is harder to push someone off when they’re sitting with you in the company cafeteria. And in a post-COVID world where founders got comfortable selling over Zoom, the willingness to show up sets you apart more than most people realize.

People buy from People

One CIO told me recently that he now requires an on-site visit before signing any AI vendor. Not to evaluate the product. To make sure he’s buying from a real person and the face he’s seen on the Zoom isn’t a bot! I expect this to be a common ask going forward.

Because until AI is buying from AI, people still want to buy from people. And the faster they stop checking your work, the faster you’ll earn their business. Whatever your product does, there’s a version of trust signal in your usage data. Find the behavior that shows a customer has stopped second-guessing you, and track it like you track revenue. And shorten the time to trust as much as possible.

On Thursday, Jack Dorsey announced Block is cutting 40% of its workforce, more than 4,000 people, because “intelligence tools have changed what it means to build and run a company.” Block surged in after-hours trading.

Both stories pointed to the same thing: AI replacing large swaths of the workforce. The fictional version caused panic. The real version caused a rally. That disconnect is worth sitting with.

A few things can be true at once

AI is genuinely changing how companies are built and operated. The capabilities are real, they’re compounding, and organizations will look meaningfully different because of them.

And *also*, Block had roughly 3,900 employees at the end of 2019, which ballooned past 12,500 in 2022. Layoffs have happened in 2023, early 2025, and again earlier this month.

So when the explanation for cutting nearly half the company is AI, it’s fair to ask: how much of this is the future arriving, and how much is the past catching up?

To his credit, Dorsey acknowledged that Block over-hired during COVID and that he “incorrectly built 2 separate company structures (Square & Cash App) rather than 1.” That’s an honest admission and an important one.

The answer at Block is that multiple things likely are happening at once. AI is genuinely enabling smaller teams to do more. The company grew too fast and made expensive bets at the peak. And maybe a hard reset is the only way to rewrite the playbooks for what comes next. All of those things can be true. But framing can turn the same set of facts into either a selloff or a surge.

Enter the AI Brush

A brush can paint something new on a blank canvas. It can also cover up blotches and mistakes. AI has become a very convenient brush. That part isn’t new. Every cycle has a narrative that makes painful corrections feel strategic:

2001 → “dot-com reset”
2008 → “financial discipline”
2020 → “COVID realignment”
2025/2026 → “AI-native transformation”

When the dominant narrative is that AI is reshaping everything (and it is), it becomes easy to fit your company’s story into that narrative. Over-hired during COVID? That’s not a correction, that’s an AI-native reset. Multiple rounds of layoffs? Not a pattern, a transformation. The narrative is so powerful right now (and changing so quickly) that most will nod along because it matches what they’re already reading and hearing everywhere else. It’s a great way to reinforce a version of reality that may not be quite right.

As Wharton’s Ethan Mollick noted, given that effective AI tools are genuinely new, it’s difficult to believe that any organization has unlocked a sudden, firm-wide 50% productivity gain in under two years. That doesn’t mean AI isn’t a factor. It means it probably isn’t the only factor.

Markets are reinforcing the pattern

A fictional scenario about AI layoffs tanks stocks. An actual announcement of AI layoffs sends shares soaring. The fictional scenario implied collapsing demand. The real one implied expanding margins and operating leverage.

Dorsey himself said he thinks most companies will reach the same conclusion within a year. He might be right. This is going to ripple. Every CEO who watched Block’s stock surge 24% on a 40% headcount reduction is now looking in the mirror and asking themselves what their version of this announcement looks like. And the ones who are honest with themselves will separate what AI actually changes from what was already broken. But you’ll likely see everyone reach for the AI Brush.

So as more of these announcements land, it’s increasingly important to read past the headline and spend time deciphering what AI is genuinely changing and what is simply being rewritten under its banner. The answers are usually in the footnotes, not the press release.

They were paying for him.

They wanted him embedded as a fractional executive for a few months to help shape their AI and data strategy. Not advising from the sidelines, but in the room, helping drive decisions across the organization.

I’ve been chewing on the implications.

The Origins of FDE

Forward Deployed Engineers were pioneered by Palantir: instead of throwing software over the wall and hoping for adoption, you put engineers on the ground who understand the customer’s problems and can bridge the gap between what the product does and what the customer needs.

It’s been copied across the industry. And it works.

But I wonder if we’ve been thinking about the acronym too narrowly. What if FDE stood for Forward Deployed Executive?

In most organizations, especially smaller orgs outside of the tech bubble, there’s no single person who owns AI or data strategy. The most senior technical person is an IT leader, who most people associate with keeping systems running (networking, devices, security). They’re essential, but focused on infrastructure, not transformation. They’re not thinking about customer data as a source of strategic leverage, or how AI could reshape operations or unlock new revenue streams. That’s simply not the remit.

So when these organizations decide they need to “do something with AI,” there isn’t a natural person to lead the charge.

That gap can become a founder’s opportunity.

What “True Partner” Actually Means

If you can fill the leadership vacuum within a customer’s organization, you become something more than a vendor. Customers start treating you (and hopefully your team) as an extension of their own.

And when you’re embedded that deeply, you see their problems firsthand. You understand the constraints, the politics, the real blockers that never make it into a requirements doc. That knowledge flows directly into your roadmap. A better product creates more value. More value builds trust. Trust pulls you in deeper. And the flywheel turns.

The Evolution of FDE

Every founder talks about wanting to be a “true partner” to their customers. It’s almost a throwaway line at this point.

The vision in most folks’ heads of an FDE is someone young, scrappy, who can be thrown into uncomfortable situations. But the trade-off is that they are excellent at mapping out the minutiae, yet may not be a credible executive partner to the client. You make up for that by having lots of FDEs on-site.

But maybe a different bar has been set: your customer is willing to pay for your judgment, not just your product, and give you a seat at the table where decisions get made. This also takes advantage of more seasoned operators who can bring something different to the table. Less “I will grind through anything to make this work”, more “I’ve seen this before and have well formed opinions you trust.”

I’m not sure how many customer relationships can reach that level, but it’s worth asking which ones are closest, and what it would take to get there.

FDE. Same acronym. Different meaning. Or maybe FDX?

Thank you to Daniel S. for feedback on this post.

Today, that psychological threshold got a financial stamp of approval.

Insurance company Lemonade announced they’re launching Autonomous Car Insurance, cutting premiums by roughly 50% when FSD is engaged. From the announcement:

The new offering cuts per-mile rates for FSD-engaged driving by approximately 50%, reflecting what the data shows to be significantly reduced risk during autonomous operation. Lemonade expects further reductions as Tesla releases FSD software updates, which are anticipated to make the cars even safer over time.

And later:

“Teslas driven with FSD are involved in far fewer accidents,” [Lemonade President Shai] Wininger added. “By connecting to the Tesla onboard computer, our models are able to ingest incredibly nuanced sensor data that lets us price our insurance with higher precision than ever before.”

“Beyond the product announcement today, we’re also announcing our commitment to the Tesla community – the safer FSD software becomes, the more our prices will drop,” Wininger said.

I admit I reread the price decrease a few times to confirm. This is not a 5% drop. It’s fifty percent. The data is so compelling that Lemonade is willing to take in less in premiums because that's how confident they are that they will have to pay out less in losses. Talk about an amazing case study of how AI and robotics deployment within one category can reshape adjacent industries.

First Mover Advantage

Insurance is fundamentally about pricing risk. The better you can predict outcomes, the more precisely you can price coverage. Lemonade is betting real money that FSD miles are safer than human miles - safe enough to cut rates in half while still maintaining profitable loss ratios.

This isn’t just a new product announcement, it’s a very competitive move. Traditional insurers are grappling with how to price coverage in an increasingly autonomous world. Lemonade is using AI to price AI and believes they will lead the industry going forward.

Now, committing to lower prices further as Tesla releases FSD updates that improve safety can be taken as a brilliant customer acquisition gamble versus genuine confidence in the data. My guess is it’s both. Other insurers will watch closely. If Lemonade starts to attract customers and loss ratios hold or improve, expect to see this roll out more broadly across the industry as traditional underwriting models built on driver age, ZIP code, and proxies start to look obsolete.

An Important Milestone

It is still early in the autonomous driving world. There are between 5 and 6 million Teslas on the road with FSD capabilities, FSD still requires driver supervision, and full autonomy is still probably years away. Even Autonomous Car Insurance will only be available in Arizona and then Oregon to start.

But milestones matter. And an insurance company pricing autonomous miles at half the rate of human miles is a meaningful one toward an increasingly AI-driven (pun intended) future.

Repricing Reality

The question my son asks about the car not driving itself applies more broadly: why isn’t [insert industry] doing this yet? Often, the constraint isn’t capability. It’s the gap between what technology enables and what we’re willing to let it do.

But when we deploy AI and robotics into industries where humans currently operate, adjacent systems and supporting industries have to adapt. Insurance is an obvious example. But across manufacturing, healthcare, logistics, food service - any industry with physical human risk - will need to rethink how they price, regulate, and organize around more intelligent machines.

We will need to reprice reality.

Tipping Points

Volvo just unveiled their new EX60 electric SUV. Impressive range, fast charging, premium interior. But only ‘driver assist’ features, no self-drive.

At this point, that’s a dealbreaker for me (and I’m guessing for a large and growing number of drivers). Should insurance prices continue to fall with autonomy, “driver assist only” stops being a neutral product decision and becomes a tax. And when the absence of a technology becomes more notable than its presence, you’re past the tipping point.

N.B. In another example of regulation being behind the times, according to Lemonade California will likely not see this product in market for a while thanks to Prop. 103. Passed in 1988, this piece of legislation, among other things, prohibits insurance companies from pricing insurance based on telemetry data. Ironically (?) it was originally passed to protect consumers, lower costs and create a better insurance market 🤦🏽‍♂️

“Friends congratulate me after a quarterly-earnings announcement and say, ‘Good job, great quarter,’ and I’ll say, ‘Thank you, but that quarter was baked three years ago.’ I’m working on a quarter that’ll happen in 2021 right now.” - Jeff Bezos

Founders operate ahead of the company. That’s the job. Seeing around two corners, making sense of the noise, setting the vision for a future that doesn’t exist yet. And while early-stage companies aren’t as predictable as Amazon, the principle holds: you’re usually working on things that haven’t happened yet.

That Series A that is closing next week? You’ve spent the last 6 weeks living and breathing decks, coffee chats, term sheet negotiations and diligence, all while trying to close more customers. That major product launch? You first came up with the concept when you conceived of the company. The critical hire who finally signed? You started courting them a year ago.

By the time any major moment lands, it doesn’t feel like a ‘win’. It feels like an inevitability, something set in motion long ago. You have processed these already and moved on.

Your team hasn’t.

The Context Gap

As a founder, you have context nobody else has. You’ve been planning and playing three moves ahead while everyone else has been executing move one. To you, milestones are confirmation that the plan is working. To your team, they can mean something entirely different.

They’re proof that the long hours mattered. That the risk was worth taking. That the sacrifices make sense, not just internally, but to the people in their lives who ask, “How’s work going?”

When wins go unacknowledged, that story gets harder to tell.

Take a Beat

This isn’t to say you should manufacture celebrations or be constantly congratulating people. But when something meaningful takes place, something that once kept you up at night, pause and mark the occasion.

Ring a gong. Send a company-wide Slack message. Call an unscheduled all-hands. Go out to dinner. Take a team photo. Create a small piece of swag tied to the moment. One portfolio company wired a gong to Slack with a Raspberry Pi so every hit sent a message to the entire team, remote included.

The action doesn’t matter.

The pause does.

These moments become the stories your team tells about the company. “Remember when we closed that impossible customer?” “Remember when we finally shipped V2?”

That shared history carries teams through the inevitable rough patches. It becomes part of the culture, evidence that progress happens, even when it’s not necessarily obvious day to day. And remember, as the company progresses what qualifies as a milestone will too. One day you’ll be celebrating a $1M quarter. The next you’ll be marking a $1M day.

Celebrate the wins. You’ll thank yourself later.

What are fun ways you’ve celebrated the wins with your team?

A warm welcome to new readers getting this for the first time, and thank you for letting me be a small part of your week! As a reminder, I’m Rishi Taparia, Co-founder and General Partner at Garuda Ventures, a first-check fund that partners with founders as they pull the future into the present. Tippets is a curated set of tidbits and snippets (get it…tippets…) from my reading around the web.

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Tippets from Around the Web:

The “ChatGPT moment” has arrived for manufacturing

Artificial intelligence is making factories smarter and more flexible by helping robots do many tasks and work alongside humans. New software and AI models improve robot accuracy and allow smaller, more efficient factories near cities. This change may lead to safer, faster, and more local manufacturing than ever before.

Generative AI promises to take this transformation a step further. Until recently, precisely modelling the actions of a robot was often impossible owing to the many variables involved, a problem known as the “sim-to-real gap”. Simulations tended to break the moment lighting or the shape of an object changed. Supersized AI models, trained on vast amounts of data from sensors and cameras, may help solve that. As simulations become more accurate and detailed, it may be possible to program robots to approach a physical task much as a human would, perceiving, understanding and then reacting to the situation.

(6-minute read, The Economist 🔒)

Standing Out in 2026

A terrific piece by Lulu Cheng Meservey on the value of being real in an increasingly ‘fake’ world, and why putting in real effort will help individuals and companies rise above the noise and more effectively share their message with their target audience.

In this world, the real has never been more precious, refreshing, special, rare. What stands out are real people, building real things that actually matter, through real discipline and effort, with real outcomes in the real world.

(2-minute read - X)

Sometimes Athletes Just Get Lucky

Interesting read on how athletic success depends not only on talent and hard work but also on luck. A good reminder to parents and teams should remember this and avoid harsh early selections, keeping opportunities open for all players.

To Baker, these models suggest that it’s not just hard to reliably predict athletic futures; it’s impossible. He cites examples including a youth-soccer player for Northampton Town who missed a text message from the team’s manager telling him that he’d been dropped from the roster for an upcoming game. He showed up for the bus, went along for the ride, subbed in when another player got injured, impressed the manager, earned a spot for the rest of the season, and went on to play in the Premier League. Luck takes many forms, such as genetics, family resources, and what sports happen to be popular at a given place at a given time. But sometimes, it’s simply random chance: a gust of wind or an errant bounce or a missed text.

(6-minute read - The Atlantic)

The war for minerals, oil and AI

The U.S. remains heavily dependent on China for rare earths, creating both economic and geopolitical risk. Securing alternative sources, like those in Venezuela and Greenland, could meaningfully strengthen American leverage and long-term competitiveness. That said, mining is only half the battle as refining and processing capacity is still overwhelmingly concentrated in China. But an added wrinkle to the moves by the US government this week.

(4-minute read - Axois)

Gmail is entering the Gemini era

Google surpassed Apple as the second most valuable company in the world this week, crossing $4T in market cap. They also made a long-awaited announcement regarding Gmail and new AI features. Coming to users soon, Gemini in Gmail will now help users manage their inboxes, summarizing email threads, suggest replies, and highlight important messages. I personally believe Google and its associated products will be how most of the world experiences AI for the first time, and I’m excited to see this roll out to the masses.

(3-minute read - Google)

Quote I'm thinking about: “So, how do you make a game? The same way you make any other worthy contribution to this strange and beautiful world we are fortunate enough to share, however briefly. You put yourself on the hook. You fill the gap in the universe only you can see. You use your gifts to make gifts for people you care about.” - Eliot Peper, Ensorcelled

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My seven-year-old asked me this the other day. Same questioning tone as when he caught me hand-washing dishes last year after the dishwasher broke. Over the last six months since we got our Model Y, self-driving isn’t the future to him - it’s just how cars work.

When we first got the car, both kids (and my wife and I, perhaps less audibly) would shriek with delight when I’d lift my hands off the wheel. “The car is driving itself!”

That sense of wonder lasted maybe four weeks. The magic wore off, not because it became less impressive, but because we adjusted to the new normal faster than any of us expected.

The surprise wasn’t that the technology worked. It was how quickly wonder turned into expectation.

We Pushed the Button and Off We Went

Over the holidays my wife commented on how fast our family adapted to Full Self-Driving.

There wasn’t a revelation moment. It wasn’t because I’d read about FSD12’s new approach, or found safety data convincing (one collision per 5 million miles with FSD versus one per 700,000 miles for human drivers).

We got the car, I pushed the button, and off we went.

Within a few weeks, I was using it almost all the time.

The Drive Became Part of the Evening

Over the holidays we drove to a holiday party in Saratoga - what Google Maps said would be a 90-minute drive at night in the rain. Normally I’d dread this drive, maybe skip the party entirely. (My general rule: if transit time exceeds event time, skip). There and back was shaping up to be 2.5 hours driving for 1.5 hours of holiday partying.

But it was fine. Better than fine. The kids were entertained in the back. My wife and I actually had a robust and engaged conversation since I wasn’t white-knuckling through rain on unfamiliar roads. The drive became part of the evening, not the cost of admission.

That’s what’s hard to explain to people who haven’t tried it: it’s not just about a safer drive. It’s about cognitive load. FSD removes the constant low-level stress - the attention, the decisions, the monitoring. You’re still present and responsible, but you’re not doing it anymore.

This is why, of all the “purchases” I’ve made in the last year, FSD has most improved my daily life.

My kids? Believers.

My wife? She’ll ride with me using it no problem, and has slowly started using it herself.

My parents and in-laws? Hard pass. With convincing, they will sit in the passenger seat, but definitely won’t get behind the wheel with it on.

The Passenger Seat Tells You Everything

The statistics about a better drive are overwhelming, but data won’t override instinct about ceding control. Whether or not you buy the exact numbers isn’t the point. Even if FSD were only marginally better, the psychological hurdle would remain. Even though we happily hand over control with every flight, every Uber ride, every train trip - being in the driver’s seat while not driving feels different.

That distinction matters. As a passenger, it’s easy to rationalize FSD: someone else is “responsible,” even if their hands are off the wheel. But behind the wheel themselves and not actually driving? That’s ceding control in a way that feels fundamentally different.

This isn’t really about FSD. It’s about control.

FSD (and AI more broadly) asks us to trust algorithms instead of humans. For many people, that feels categorically different. Not because algorithms are less capable or worse at performing a task (in self drive’s case the data says the algo is meaningfully better) but because trusting a computer takes more than data to build in a way that trusting a stranger doesn’t.

Research from MIT confirms this: we tolerate human error as randomness; we interpret algorithmic error as design failure.

So in my view the real barrier to AI adoption, with self-drive as perhaps the most direct question is not capability (these systems already do remarkable things) or safety (in many domains, AI already outperforms humans) but psychology: will you cede ultimate control to something that isn’t human?

For me and self-driving, the answer is yes.

For the next generation? Bruh, cars just drive themselves.

Will My Kids Need Driver’s Licenses?

For years I’ve asked friends: will our kids need driver’s licenses? Mine are seven and five, so we’re talking about a decade out.

I used to think no. Now I think yes - but not because of technology, but because of the barriers to technology adoption.

As Alan Slutkin notes, in the car context we’re holding self-driving to an impossible standard - expecting perfection while accepting almost 40,000 annual deaths from human drivers. The question isn’t whether autonomous vehicles are perfect. It’s whether they’re better than humans. And increasingly, they are.

Technology will advance faster than regulation, faster than social consensus, faster than our collective comfort. My kids probably will need driver’s licenses - not because they’ll need to drive, but because we haven’t closed the gap between what technology can do and what we’re willing to let it do.

But I think about my son asking why the car isn’t driving itself, like asking about any household appliance. For him, self driving cars have nothing to do with humans ceding control. He never assumed humans had to be in control in the first place.

That’s the future already here in my driveway.

Where in your life are you still holding the wheel not because you need to, but because letting go feels uncomfortable?

A warm welcome to new readers getting this for the first time, and thank you for letting me be a small part of your week! As a reminder, I’m Rishi Taparia, Co-founder and General Partner at Garuda Ventures, a first-check fund that partners with founders as they pull the future into the present. Tippets is a curated set of tidbits and snippets (get it…tippets…) from my reading around the web.

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From Me This Week:

Tippets from Around the Web:

2025 letter

Dan Wang (author of Breakneck, one of my top books of 2025) published his annual letter this week. Worth sitting down with a cup of coffee and reading in full, he talks all things Silicon Valley, AI, and warns the U.S. underestimates China’s industrial strengths and rapid AI progress.

Though San Francisco has produced so much wealth, it is a relative underperformer in the national culture. Indie movie theaters keep closing down while all sorts of retail and art institutions suffer from the crumminess of downtown. The symphony and the opera keep cutting back on performances — after Esa-Pekka Salonen quit the directorship of the symphony, it hasn’t been able to name a successor. Wealthy folks in New York and LA have, for generations, pumped money into civic institutions. Tech elites mostly scorn traditional cultural venues and prefer to fund the next wave of technology instead.

(54-minute read - Dan Wang)

The Prison Of Financial Mediocrity

A thought-provoking read digging into why we are seeing the rise of betting / prediction markets, as young people turn to high-variance bets (crypto, prediction markets, sports betting) as a way to gain agency in todays world.

White-collar workers, or otherwise the financially aspirational, are watching the timeline shrink. Three years ago, “AI will replace knowledge workers” was a thought experiment. Now it’s a planning assumptioem>n. Everyone’s asking when, not if, and the estimates keep getting shorter.

Then there’s social media, which ensures you’re never satisfied with where you are. The algorithm is optimized to show you the next tranche of what could be. Always the vacation you haven’t taken. The apartment you can’t afford. The lifestyle one rung above yours. It doesn’t matter where you are on the ladder; there’s always someone above you, and the algorithm will find them.

Previous generations had limited visibility into how others lived. You compared yourself to your neighbors, your coworkers, maybe some celebrities in magazines. The reference class was narrow. Now the reference class is infinite. A 25-year-old making $70k is constantly fed content from people their age making $2mn, living in Bali, “working” four hours a day. The baseline for “enough” keeps moving.

You never catch up. No matter what you achieve, social media will show you what you’re missing. The spread between your life and the life you “should” have is maintained algorithmically, forever uncollapsible.

So you have AI shrinking your timeline AND social media ensuring you never feel like you’ve arrived. The pressure to escape, NOW, FAST, before it’s too late, compounds daily.

(10-minute read - Sysls on X)

Side Quest Recommendation: "The Story of Civilization" Series [Durant]

The latest reminder of the benefits of reading, and reading widely with some very practical advice on how to find more time to read more.

⁠⁠Munger talks about the "latticework of mental models." I thought I understood this concept at a younger age, and I definitely DID NOT. Because the way you develop this latticework is to read widely across non-investing, non-market, non-business material.

⁠⁠There is no shortcut to the latticework. It can only be developed through reading wide and deep, and it pops into place organically.

Don’t be a passive observer to your own life. The way I’d put it is that if you don’t actively take charge of your own time, you will keep doing the exact same shit you are doing, every single day, until the day you die.

(14-minute read - Gregory Blotnick on X)

Capital in the 22nd Century

A thought-provoking piece on AI and the future of income and wealth inequality. If AI makes capital a true substitute for labor, authors Philip Trammel and Dwarkesh Patel argue wealth will concentrate in the hands of those richest when that shift happens. Without a strong global progressive tax on capital or capital income, inequality could grow without bound and be inherited. Capital-driven growth may boost overall output but will make taxing capital costly and politically hard.

(35-minute read - Substack)

Quote I'm thinking about: “All your uses of time should be benchmarked to reading books. There is nothing more valuable, nothing, nothing, nothing.” - Gregory Blotnick

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2025 in the books, fifteen books completed during the year. This was a year where golf made a triumphant return to my life and to my reading list with a number of books that explored both the technical and philosophical sides of the game. I also made a conscious decision to read less non-fiction this year, though I realized I could still use more fiction recommendations (especially in the sci-fi realm after Project Hail Mary blew me away).

As always, below is the list of fifteen books from 2025 with quick thoughts on each. As I pull together my reading list for 2026, please click the link below and send me your book recommendations!

And for my past years’ reading lists, click here.

Recommend a book!

Note: * indicates a strong recommendation

Fiction

Project Hail Mary by Andy Weir*

One of my favorite reads of the year, Project Hail Mary exceeded all expectations. From the author of The Martian, the story of Ryland Grace waking up on a spaceship with no memory, tasked with saving humanity, is equal parts scientifically fascinating and emotionally gripping. The combination of hard science with deep humanity and humor with existential stakes made this an absolute must-read. And I’m excited for the movie coming this year!

Station Eleven by Emily St. John Mandel*

A post-apocalyptic novel that feels less about the collapse and more about what endures. Set in the aftermath of a devastating flu pandemic, the story follows traveling symphony performing Shakespeare twenty years after. Mandel weaves together multiple timelines to explore art, memory, and survival. The story’s central questions focus on what matters when civilization falls and answers that beauty, art, and human connection matter more than ever. This one stayed with me long after I finished it, a great read.

Ensorcelled by Eliot Peper

More of a novella, Ensorcelled is described as a “campfire fable for the digital age” that asks readers to reconsider the true meaning of magic. Set in the near future, the novella follows a teenage gamer, Tam, who is forced by his family to trade his highly anticipated game launch for a tech-free camping trip. Here, Tam discovers a deeper, more demanding kind of “magic” in the wilderness: the art of being fully present. A great exploration of the interplay between a digital life and the raw, essential rewards of the physical world. A great, quick read.

The Cuckoo’s Calling by Robert Galbraith

Robert Galbraith is better known as J.K. Rowling. This first foray into detective fiction introduces us to Cormoran Strike, a war veteran turned private investigator who is tasked with looking into the death of a supermodel. The story has classic detective novel beats, but Rowling’s character work elevates it beyond typical genre fare. Strike is wonderfully flawed and thoroughly engaging. A solid detective story that will certainly have me continue with the series in 2026.

Dead Lions by Mick Herron

I started reading Slow Horses series last year and thoroughly enjoyed continuing it in 2025. The second installment finds the disgraced MI5 agents investigating a Cold War era sleeper agent. Herron’s plotting is as intricate as ever, with threads that seem disconnected slowly weaving into a satisfying whole. The flashbacks to Cold War spy craft provide interesting contrast to the bureaucratic dysfunction of modern intelligence work. Another excellent entry in a series that keeps getting better.

Real Tigers by Mick Herron

Continuing my journey through the Slow Horses series, Real Tigers delivers more of Herron’s trademark wit and intricate plotting. The “slow horses” find themselves dealing with a kidnapping that hits uncomfortably close to home. Herron’s ability to blend espionage thriller mechanics with dark humor and genuine pathos keeps this series fresh. The dialogue is sharp, the plot twists satisfying, and Jackson Lamb remains one of the most entertaining characters in modern spy fiction.

The Secret of Secrets by Dan Brown

As my friends know, I love me a Dan Brown book. Call it a vice, call it a love of mystery coupled with ancient symbols and secrets, it doesn’t matter. Dan Brown returns with another Robert Langdon adventure, this time involving ancient secrets and modern conspiracies. It hits many of the familiar beats (symbology, historical mysteries, breathless pacing) and is an entertaining page-turner that doesn’t demand too much. Perfect airplane reading (which I definitely needed this year) that keeps you engaged without requiring deep investment.

Trust by Hernan Diaz

A novel told in four nested narratives, each revealing new layers of truth about a wealthy financier couple in 1920s New York. Diaz’s structure is ambitious, moving from novel to memoir to autobiography, and forces you to question everything you’ve read. It’s a meditation on truth, power, and who gets to write history. The writing is elegant, the construction ingenious, and the questions it raises about narrative reliability linger long after the final page.

The Legend of Bagger Vance: A Novel of Golf and the Game of Life by Steven Pressfield

The Legend of Bagger Vance is a perfect meditation on golf as metaphor for finding one’s authentic self. Set in Savannah during the Depression, the story of Rannulph Junah’s return to golf with the help of the mysterious caddie Bagger Vance is less about technique and more about surrender, presence, and the search for one’s “Authentic Swing.” Vance’s wisdom about letting go of the ego, trusting the swing that already exists within you, and approaching the game with love rather than fear provided a philosophical framework that complemented the practical advice of Sherman and Rotella. It’s a quick, lyrical read that has lessons which extend well beyond 18 holes.

Non-Fiction

Chip War: The Fight for the World’s Most Critical Technology by Chris Miller*

This is essential reading for understanding the modern geopolitical landscape. Miller traces the history of the semiconductor industry from its origins to its current status as the most strategically important technology on Earth. The book brilliantly explains why chips matter, how they’re made, and why control over their production has become the central struggle between the United States and China. Dense with information but never dry, it’s a masterclass in making complex technical and geopolitical subjects accessible. Reading about the steep competition between the US and Japan in the 80s, I was struck by the similarities in the discourse and dialogue around today’s AI race, and the US and China. Chris Miller needs to write a follow-up to as eloquently explain what’s going on today with the chip fight in AI land!

Breakneck: China’s Quest to Engineer the Future by Dan Wang*

Dan Wang’s deep dive into China’s engineering-driven approach to development is fascinating and nuanced. Rather than viewing China exclusively through the lens of Beijing politics or American assumptions, Wang examines how the country’s focus on physical infrastructure and manufacturing has reshaped its economy and society - the lawyerly society vs the engineering society. He challenges conventional wisdom about innovation, showing how China’s emphasis on process knowledge and manufacturing excellence represents a fundamentally different model than Silicon Valley’s virtual economy. A solid read for anyone trying to understand U.S. - China competition and how the governing styles will influence the next 20 years of competition.

The Four Foundations of Golf: How to Build a Game That Lasts a Lifetime by Jon Sherman

Jon Sherman’s approach is refreshingly data-driven and practical. Rather than promising quick fixes or secret techniques, he focuses on sustainable improvement through smart strategy and realistic expectations. His emphasis on course management over swing perfection was helpful, and he focuses on the idea that you don’t need to hit perfect shots to score well, you just need to avoid big numbers. The book also does something rare in golf instruction: it acknowledges that most of us aren’t going to practice five hours a day, and builds a framework around that reality. If you’re looking to actually improve your scores rather than just your swing, this is the book.

Golf is Not a Game of Perfect by Bob Rotella

Bob Rotella’s classic is required reading for anyone serious about golf. The core message (that golf is primarily a mental game) isn’t new, but Rotella’s articulation of it is brilliant and, like Bagger Vance, has application beyond the game of golf. The book helped me understand that confidence isn’t something you’re born with, it’s something you cultivate through how you think about your game. His emphasis on staying in the present, accepting whatever swing you brought to the course that day, and focusing on targets rather than mechanics transformed how I approach each round and day to day challenges in general. The concept of the “unconsciously competent” golfer (someone who trusts their swing rather than thinking their way through it). This book pairs perfectly with Sherman’s strategic approach: Sherman tells you what to do, Rotella tells you how to think while doing it.

(Auto)Biographical:

Who Is Michael Ovitz? by Michael Ovitz*

This is an amazing look at a titan of industry through his own words. A brisk tour of how he turned CAA into Hollywood’s power center. Deal vignettes - Jurassic Park, NBA TV rights, corporate tie-ups - reveal his playbook: out-prepare rivals, surround talent with 360° service, and use psychology as leverage. A masterclass in deal-making, accumulating power, and a seemingly relentless drive, it is almost certain that Ovitz would have been successful at whatever he put his mind to. It is also a cautionary tale - the same control that fueled CAA’s rise doomed his short, infamous run at Disney. An entertaining read!

Spiritual/Philosophical:

The Bhagavad Gita translated by Stephen Mitchell*

I read the Gita this year for the first time. Admittedly, it required a new way of reading, stopping to pause and reflect on the dialogue between Krishna and Arjuna on the battlefield. It is ostensibly about duty and war, but the teachings are really about how to live, how to act without attachment to outcomes, how to find peace in the midst of chaos, how to reconcile action with spiritual understanding. I thought it was a wonderful translation, and worth reading giving the enduring nature of its message.

The Courage to Be Disliked by Ichiro Kishimi and Fumitake Koga

Presented as a dialogue between a philosopher and a cynical young man, this book introduces Adlerian psychology’s radical ideas about freedom, interpersonal relationships, and happiness. The core insight (that we are not determined by our past but by the meaning we assign to it) is liberating. The book’s emphasis on “separation of tasks” (distinguishing what is your responsibility from what belongs to others) and the idea that “freedom is being disliked by other people” challenged my thinking about approval-seeking and living authentically. Some of the ideas feel extreme, but I think that’s partly the point: they’re designed to shake you out of conventional thinking. A thought-provoking read that pairs well with the Gita’s teachings on detachment.

Quote I'm thinking about: "You have a right to your actions, but never to your actions' fruits. Act for the action's sake. And do not be attached to inaction." - The Bhagavad Gita

Happy holidays! A warm welcome to new readers getting this for the first time, and thank you for letting me be a small part of your week! As a reminder, I’m Rishi Taparia, Co-founder and General Partner at Garuda Ventures, a pre-seed focused fund that partners with founders as they pull the future into the present. Tippets is a curated set of tidbits and snippets (get it…tippets…) from my reading around the web.

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Tippets from Around the Web:

AI’s trillion-dollar opportunity: Context graphs

A great piece by Jaya Gupta of Foundation Capital illustrating how context is key when thinking about AI Agents and the opportunity in front of them. Agents won’t replace systems of record, instead they will become the interface on top of these systems. The key, however, is their understanding of the underlying decision history. That “context graph” can become the new system of record and major commercial platforms.

(9-minute read - Jaya Gupta)

Silent Sirens, Flashing For Us All

Jack Clark, co-founder of Anthropic, talks eloquently about why everyone needs to be playing and using AI more than we already are. AI is “naturally illegible”, and requires agency, time, and curiosity. We will all benefit from spending more time with it.

⁠Most of AI progress has this flavor: if you have a bit of intellectual curiosity and some time, you can very quickly shock yourself with how amazingly capable modern AI systems are. But you need to have that magic combination of time and curiosity, and otherwise you’re going to consume AI like most people do - as a passive viewer of some unremarkable synthetic slop content, or at best just asking your LLM of choice “how to roast a turkey and keep it moist”, or “TonieBox lights spinning but not playing music what do I do?”. And all the amazing advancements going on are mostly hidden from you.

(5-minute read - Jack Clark)

Steam, Steel, and Infinite Minds

A well-researched article by Notion co-founder Ivan Zhou on why AI is this generation’s miracle material and will require driving to the future looking forward, not, as Marshall McLuhan describes it, “via the rearview window.”

AI is steel for organizations. It has the potential to maintain context across workflows and surface decisions when needed without the noise. Human communication no longer has to be the load-bearing wall.

⁠We're still in the "swap out the waterwheel" phase. AI chatbots bolted onto existing tools. We haven't reimagined what organizations look like when the old constraints dissolve and your company can run on infinite minds that work while you sleep.

(6-minute read - Ivan Zhou)

Jevons Paradox for Knowledge Work

Aaron Levie, Box’s CEO, makes an optimistic case for AI, arguing that while AI will make knowledge work much cheaper, the opportunity is not fewer tasks, but more. Thus, small teams and startups can now afford work that only big firms could before, and this surge in demand will create new projects, jobs, and uses we can’t fully imagine today.

(5-minute read - Aaron Levie)

The hidden forces ruining youth sports

Back in the day, youth sports were about playing with friends, learning teamwork, and maybe getting a snack after the game. As a dad now, I see a very different picture, with higher costs, intense competition, and a focus on winning that can lead to stress or injuries for kids. Families often spend a lot hoping for scholarships that most young athletes will never receive. I can’t help but miss when the game was just about the love of playing.

(6-minute read - Vox)

Quote I'm thinking about: “We shape our tools and thereafter our tools shape us.” — Marshall McLuhan

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One moment you’re walking out of a customer meeting having just agreed on terms for a multi-year contract that you’ve been through the ringer on with legal, their finance and procurement teams. You walk into your next meeting, a 1:1 with one of your top engineers expecting to talk product roadmap. And that’s when they let you know they’ve accepted an offer from another company.

Down we go.

The Gut Punch is Real

When someone leaves, particularly when you’re still a small team, it can feel devastating. You’ve worked late nights together on getting a customer feature rolled out before a demo. You’ve traveled to conferences looking to drum up new leads. You’ve recruited other people to the team.

This person wasn’t just an employee, they were a believer. Someone who signed up for the uncertainty, the lower pay and equity that might never be worth anything, the long hours and the constant adapting to the market. And now they’re...leaving?

It can feel like a betrayal.

The emotional reaction is understandable, but it’s also important to remember not to take it personally.

Step 1: Figure Out if They Can Be Saved

Before you spiral, take a breath and ask yourself: Is there a way to convince them to stay?

Most often, the answer will be no. By the time someone sits you down for “the conversation,” they’ve typically already mentally moved on. They’ve gone through an entire interview process, negotiated terms, and made a decision. And then they have gathered the courage to finally tell you. That’s a lot of psychological momentum to overcome.

But it’s worth exploring. Maybe there’s something you can address - a role change, additional responsibility, a compensation adjustment, or even just a more flexible work arrangement. However, be honest with yourself about whether any fixes would be sustainable, and perhaps more importantly, fair to the rest of your team. Paying one person significantly more than others, for example, or giving them special privileges to stay often creates more problems than it solves.

Step 2: Understand the Why

Assuming they’re truly committed to leaving, your next job is to understand why. And I mean really understand, not just accept their polite explanation about “pursuing new opportunities.” Because, for someone to leave a startup they previously believed in, a concrete sequence of events had to take place:

1. Something changed at work that made them question their fit, growth trajectory, the opportunity ahead for the company, etc.

2. They became more amenable to taking calls from recruiters and going through interview processes

3. They found something more attractive at another company, whether it was better compensation, more interesting work, clearer career path, better work-life balance, or simply a company they believe has better prospects

It doesn’t happen overnight. So again, don’t take their decision personally, take it as data.

Spend real time with them understanding what attracted them to the new opportunity. Was it the money? The role? The company’s trajectory? The team they’d be joining? The location or flexibility?

This isn’t about changing their mind, it’s about learning what you might need to change to retain your current team and attract more great people.

Step 3: Handle the Transition with Grace

Assuming it’s not an acrimonious departure (and hopefully it’s not), how you handle their exit matters enormously both for them and for the rest of your team.

First, make sure you create a plan for picking up their responsibilities. Nothing creates team anxiety like critical work falling through the cracks.

Second, and this is crucial: sit down with your existing team and address the departure directly. Don’t make a big deal of it, but don’t pretend it didn’t happen either. A departure can be jarring for the rest of the team, particularly when they don’t have context. It’s human instinct for people to wonder, “What do they know that I don’t know?” and potentially question whether they should stay themselves.

Be transparent: “Sarah has decided to move on to pursue another opportunity. We’re excited for her and wish her the best.” Then use that moment to reinforce why you’re building what you’re building, where the company is headed, and why the remaining team is critical to getting there. Often moments like this can serve as a rallying cry for the rest of the team.

The Long Game: Alumni as Assets

Assuming someone leaves on good terms, stay connected. Celebrate their wins. Ensure they are proud to be from your business. Some of your best customers, partners, and even future employees might come through your alumni network.

I’ve seen former employees become customers, refer great candidates, and even come back as the company grew and their career goals evolved. But this only happens if you resist the urge to burn bridges when they walk out the door.

It Gets Easier (Sort Of)

As your company grows, individual departures will sting less. When you have 5 people, having one leave can feel like the end of the world. When you have 50 people, losing one great person is meaningful but not existential.

But here’s what I’ve learned from the founders I work with: every departure, handled well, makes you a better leader. You learn what motivates people. You get better at spotting early warning signs. You build systems that make your company more resilient to key person risk.

Most importantly, you learn that people leaving doesn’t mean you or your company failed. Sometimes great people leave great companies for reasons that have nothing to do with you.

The rollercoaster will keep rolling. There will be more highs and more lows. But each time, you’ll be a little better equipped to handle the ride.

What’s been your experience with early employee departures? How did you handle it, and what did you learn? Reply in the comments below.

With Ravi, I discussed why adoption of AI in the enterprise might be slower people expect (TL;DL: It’s human psychology, not the technology, that will be the barrier).

And with Prashant, I shared the Garuda founding story, what AI disruptions of B2B SaaS looks like, and why trust is the new competitive moat.

I hope you enjoy the discussions. I look forward to your feedback!

The Batch By the Numbers

• 153 companies in the batch

• 127 AI/ML companies, with ~30 explicitly agents and 38 developer tools/infra

• 60 voice AI companies or related (a strong echo of YC’s Request for Startups which highlighted voice assistants and full-stack AI as priority areas)

• 29 hardware + hard tech companies (more than fintech and consumer combined)

• 20 healthcare/biotech companies

• 17 fintech companies (leaner than past years)

• 25 consumer companies, mostly AI-native media or networks

Some Takeaways

• Founders are getting younger: Perhaps the most striking takeaway was just how young the batch was. I lost count of the number of teams that featured founders in their late teens or early 20s, may of whom were either college dropouts or recently graduated from great schools including Harvard, Stanford, UC Berkeley, CalTech, and Georgia Tech. There was even a high school dropout in the group. And there were more sibling co-founder pairs than I expected (one founding team featured twins who memorably said they’ve known each other since before they were born! 😆)

• Alumni DNA is shifting. A number of founders have came out of Google, Meta, Amazon. But noticeably absent were alums from the current crop of frontier AI companies like OpenAI, Anthropic, or Perplexity. Most of those folks seem to be staying put (for good reason)!

• AI everywhere (obviously) but more broadly spread: 90% of the batch was AI or AI related, but there was a fairly good spread of industries including infrastructure and dev tool to healthcare and SMB. And (perhaps as a sign of the times) even a few companies dedicated to supporting PE rollup strategies

YC always offers a great read on where ambitious founders are choosing to focus. This batch makes it clear: voice is emerging as a major platform shift, agents are the next big interface, hardware and biotech need to be in the conversation, and founders are less likely to understand 2000s pop culture references than ever before. Adjust accordingly!

Welcome to Grind Time.

Rhythms of capital

From Labor Day to mid-December, the venture world transforms. Conference season kicks into high gear. AGMs take over hotels, conference halls, and in some cases, stadiums. Airport lounges are packed. And inboxes move from OOO emails to a battlefield of competing priorities.

For founders actively fundraising, understanding this seasonal rhythm isn't academic, it's strategic. Because how you get through the next 12 weeks will determine whether your round gets done this year or if we’re pushing it to 2026 (if at all).

Bring (and seek out) the heat

As a founder, it is important to realize that you need to match the energy and intensity of the market. This is not the time for slow email responses and wishy-washy follow-ups. Running a successful fundraise process requires a crisp process, tight storytelling on vision and execution, and relentless follow-up with fast turn around on data requests. And when an investor doesn’t feel like they are engaging or leaned in, move on. Because now more than ever, hoping for a slow yes can crush your momentum.

Those who are excited about the business will move diligently through the various steps in their process on the way to eventually committing. Which makes sense. If they are on board, they will not want to miss out.

The ones who aren't there will deprioritize your deal or push meetings out into weeks when they have more time (which often never happens). Or will ask for a lot of data over an elongated period of time. And you will watch as Docsend links never get clicked and emails aren’t opened, the whole time forgetting that conviction isn’t found in a data room.

Build momentum or get pushed to the backlog. There's not much middle ground.

Good luck!

To both founders and my fellow investors, good luck as we enter this season. Whatever it is you do to stay fresh - cold plunge, sleep teas, red light mask, meditation retreat, ayahuasca retreat - do it. Because it’s time to lock in!

AI Bends the Growth Curve

Bessemer’s State of AI 2025 report looks at how quickly AI companies are scaling revenue and reveals the rise of what they call the “AI Supernova”. These are companies that, on average, get to $100M in ARR in just 18 months. To put that in perspective, the best cloud companies of the past decade needed nearly 7 years to reach the same milestone.

Supernovas aren’t “fake it till you make it” businesses. They’re winning customers and scaling real revenue just on a timeline that looks almost impossible by historical standards. These are names you know like OpenAI who have reportedly crossed $10B in ARR 3 years after launching ChatGPT. Or Anthropic who went $0 to $100M to $1B (and now have cleared $4B). Amazing feats of growth and scale.

Capital is Hunting Earlier

The speed of growth explains why mega funds are now steamrolling their way into the very early-stage investors as shown in the Sapphire Partners and OpenLP analysis into the most active investors at Seed and Series A. According to the data, in 2023 the most active “mega funds” accounted for over 10% of the 2,000 priced Seed rounds that were done, with Andreessen Horowitz having led or co-led 72 seed rounds (more than double the next closest fund). And while the data isn’t perfect as it only includes priced rounds, it is likely directionally correct and the message is a clear reflection of what I’m seeing and feeling as an investor in the market: mega funds are going earlier.

Why? Because everyone wants to catch Supernovas early and so they are willing to spread bets earlier just to have a chance at the handful that break out.

The New Benchmark is Set

Here’s the truth: most companies aren’t going to be Supernovas. But with Supernovas out there, even Shooting Stars (companies that get to $3M in revenue in year one) risk looking like under performers.

Now, if you’re not at $40M ARR in year one and on a path to get to $100M 18 months from earning your first dollar of revenue, do you have a bad business? No. But you ignore the fact that this level of speed and scale is top of mind for investors at your own peril. If you’re not meeting this bar, “Why not?” matters more than ever.

So when fundraising, you need to highlight what’s durable about the business, know the numbers and the plan, articulate how you will scale into building a massive business. And proactively address (if you’re not asked) why aren’t you growing as fast as [insert your favorite Supernova or Shooting Star company].

And when debating which funds to engage with, recognize that different funds are playing different games. When raising capital, make sure you’re talking to the right ones for you, your business, and the way you want to grow.

Finally, remember that getting to $100M “overnight” is not the only way to win. As my friends over at Scale Venture Partners have pointed out, there is no correlation between speed to $100M in revenue and eventual exit size. Granted, historical data and mostly non-AI, but it does underscore the importance of durability and defensibility. Ultimately, company building is a test of survival. Speed grabs headlines. Endurance builds companies.

The future is the vision. It’s the story about where the world is headed, why the opportunity is massive, and how you and your company are uniquely positioned to capture it. Vision is what gets people excited. It sparks the imagination. Without clarity of vision, you can’t raise, no matter how good the numbers are.

But vision alone isn’t (typically) enough to close a Seed raise, and certainly not a Series A and beyond. Investors also need to know you can execute. They’re investing into today’s business and the work that will be done to achieve tomorrow’s goals. The difference between a busted process and a great round is your ability to articulate both.

Why the plan matters

It goes without saying, but a well-articulated, believable plan for how you’ll get from where you are today to the next set of milestones is essential for a successful raise. But even though it is obvious, you’d be surprised at how many founders can’t articulate what they will do with the capital once it’s raised.

Take hiring. One founder might say, “We’ll hire engineers to build out the product.” Another might say, “We’re bringing on three engineers. Two are already identified, with start dates pending the financing. One will focus on hardening the back end, and the other on tightening up the front end and user onboarding.”

Who would you invest in?

Or revenue growth. It’s one thing to say, “With this money we’ll get to $5M in ARR on the back of 100 customers with an average of $50k ACV.” It’s another to lay out the mechanics of the average deal size, expected conversion rates, length of the sales cycle, and how onboarding translates into paid contracts.

The former represents aspiration. The latter demonstrates command. It shows you understand not just the size of the opportunity, but the steps required to realize it. This kind of depth flips the investor’s mindset. Instead of asking, “Will they figure it out?” they’re asking, “What happens if I don’t invest and they do figure it out?”

Bring the future into the present

At Garuda, we often say we’re looking for founders who can paint a vision of the future and then pull that future into the present. The ability to map a 5-10 year vision to next month’s concrete deliverables separates a compelling pitch from the forgettable one.

Make the future feel inevitable, and the path to it undeniable.

Meanwhile, OpenAI and Anthropic are practically giving away their premium AI models to millions of government workers for $1 per agency, products that normally cost organizations hundreds of thousands or millions per month.

AI companies are doing genuinely unnatural things to capture users. And honestly, it's kind of beautiful to watch.

VC2C → VC2E

We've seen venture-funded land grabs before, but this feels different in scale and audacity. Remember when Uber and Lyft burned billions making rides artificially cheap? I like to call this the VC2C model: Venture Capital to Consumer. Derek Thompson later dubbed it the Millennial Lifestyle Subsidy, where companies went gross margin negative to train users to expect convenience at impossible prices. (For some great stories about that ride-sharing battle, check out my Brick by Brick interview with Amy Fox, Lyft's fifth employee.)

The AI wars are the same playbook, just for our cognitive work instead of our commute. And it's not just VC2C, it's VC2E - Venture Capital to Everyone.

In the last week:

• OpenAI goes after 2.4 million federal workers with a basically free plan

• Anthropic hits back, offering all three branches of government (3 million potential users) access for the same $1

• Perplexity puts in an unsolicited bid of $34.5 billion to buy Chrome (3.5 billion potential users) Unlikely to happen, but damn!

Why the math “works”

These companies are making a bold bet: AI switching costs are going to be higher than your average software. Once ChatGPT knows your personal or business context or Claude becomes your coding partner, changing platforms means rebuilding trust and workflows. The bet is simple: get users hooked while you have infinite access to capital at eye-watering valuations, then raise prices once they're dependent on your specific workflow. Not dissimilar to the Uber/Lyft playbook, or why legal research and design software tools are free for law students and architecture student. They learn it in school and bring it to work.

But there's a catch. This is all contingent on how much it costs to run a model. And yes, model costs are dropping dramatically.

But as points out, tokens are getting more expensive because "nobody wants yesterday's newspaper."

gpt-3.5 is 10x cheaper than it was. it's also as desirable as a flip phone at an iphone launch.

when a new model is released as the SOTA, 99% of the demand immediatlely shifts over to it. consumers expect this of their products as well.

So maybe the cost of AI won’t go down as much as we think?

Who benefits?

Premium AI capabilities that should cost thousands per month are essentially free. Investors are subsidizing our productivity just like they once subsidized our rides and food delivery. But this golden age won't last forever. The fight for AI mindshare is creating some of the most aggressive user acquisition strategies I've ever seen and once the wrestling match settles, the winners will have pricing power over users who can't imagine working any other way. And while further monetization may come in the form of ad-supported models or new usage limitations like we’ve seen Anthropic institute recently, where AI pricing nets out and the “business model of AI” is still a big unknown.

So, enjoy the investor-subsidized AI honeymoon while it lasts, because it’s not going to last forever.

The Benefits of a “Not a Board Meeting” Meeting

These quarterly sessions (let's call them "Not a Board Meetings" or NBMs for short) are different from your standard weekly or biweekly investor update calls. While monthly updates and bi-weekly check-ins with investors have the benefit of quick feedback cycles that are required at pre-seed, NBMs serve multiple purposes that these informal touchpoints simply can't match:

Clarity and accountability on what matters. Presenting the quarter’s highlights and lowlights in the aggregate requires elevating out of the day to day execution and firefighting. It forces clarity around what actually matters to distill your progress and challenges into a coherent narrative.

Stakeholder alignment. Early investors want to help, but they need context to be effective. NBMs create shared understanding across your investor group and prevent the misalignment that emerges when everyone has different pieces of the puzzle through 1:1 catch-ups that likely happen at different times and with different groups.

Story-telling practice that compounds. The discipline of crafting a data-driven quarterly narrative about your business and market, where you're going, what you're learning, makes you a better communicator with customers, future investors, and your own team.

Practice makes perfect. Learning to run an effective board meeting is a skill, and like any skill, it improves with time and practice. It is better to start developing this muscle early on, well ahead of when the board process formalizes, whether as early as seed or at Series A.

How to Run These Meetings Right

Here's the most important thing to remember upfront: The meeting should NOT be a readout of your materials. That's a waste of everyone's time, and you don’t want these to turn into “bored” meetings. The meeting should help you solve problems and make decisions. Come with real questions, share genuine challenges, and ask for specific help.

Materials that Matter

Create a template that you can update quarterly. It'll take work the first time, but each subsequent quarter gets easier. Include:

• Highlights / lowlights: The good, bad, and ugly of the quarter

• Metrics: The same key metrics every quarter so everyone can track progress and spot trends

• Business Deep-Dive: Product updates, go-to-market progress, pipeline status, new hires. Really whatever's most relevant for your stage

• Next quarter goals: Clear targets for key metrics and initiatives

• Discussion topics: 1-3 meaty subjects you want input on: pricing strategy, hiring priorities, product roadmap, anything you're grappling with. Provide context and data, then lay out specific questions for discussion.

Set Expectations and Give Time

Send materials at least 48 hours before the meeting. If you're meeting Tuesday, get the packet out Friday. This lets everyone digest the information and come with thoughtful questions rather than clarifying ones. Be explicit about expectations: "We will not be doing a page turn during the meeting. Please come prepared with questions and ready to dig into the discussion topics."

Meeting Agenda

For a two hour meeting, the below is what I’ve found to be most helpful:

• ~20 minutes: Quarter in review (highlights and lowlights, key challenges and Q&A based on materials shared ahead of time)

• ~60 minutes: Deep discussion on your one to three topics (20-25 minutes each)

• 10 minutes: Open discussion

• 10 minutes: Investor-only time for discussion

Follow up

Take notes and follow up within 24 hours. Send action items to everyone and hold people accountable to their commitments, whether that's making an introduction, providing feedback on strategy, or connecting you with a potential customer. You want to create a culture of follow-through on what you said, even at this level.

Lasting Value

Founders who establish these operating rhythms early end up dramatically better prepared when formal boards are established. They also have a stronger grasp of their business and the important metrics and milestones. They've learned to synthesize complex information into digestible updates, facilitate productive discussions among strong personalities, and use their investors as a strategic asset rather than just a reporting obligation.

Perhaps most importantly, they've created a culture of transparency and collaborative problem-solving with their investors. When challenges inevitably arise within the business (and trust me, they will) there's already a foundation of trust and regular communication in place.

NBMs shouldn't feel like performance theater with perfectly polished slides and carefully curated success stories. You shouldn't feel like you're walking into the principal's office, worried about whether you’re going to get detention. Your investors are fundamentally on your team, and it's up to you to use them as such.

Have you tried a quarterly “NBM” format? I'd love to hear what's worked (or hasn't worked) for you.

You're asking someone to leave a stable job, turn down six, seven, eight, or (and I can’t believe I'm saying this) even nine figure compensation packages to join your company where the future is uncertain, the equity might never be worth anything, and the amount of money you’ve raised might be WAY less than they would make in a year.

This isn't a sale you can show up to unprepared and shoot from the hip to close. This is convincing someone to bet their career on you and your vision. This is convincing someone to go to their spouse excited about why taking a risk joining an early-stage startup where they'll make less money, work longer hours, and generally be more stressed makes sense.

And like I have talked about before, you can't do that effectively if you're rushing through the process or treating recruiting as an afterthought.

The Stakes Are Higher Than You Think

When you're selling to a customer, the worst case scenario is they say no and you move on to the next prospect. When you're pitching an investor, a rejection means you just keep fundraising.

But when you're recruiting an early employee, this person is critical to helping scale your company and you're asking them to make a life-altering decision. The prospective employee sitting across from you isn't evaluating whether your product will help drive efficiency within their organization, or whether you have a sound go-to-market strategy. They're deciding whether you're worth betting their livelihood on. And it’s not just them you need to convince.

Sell Their Support System

One of the most important lessons I learned during my time at Poynt and Legion was this: you're not just recruiting the employee, you're recruiting their entire support system. That could be their partner/spouse. Their parents. Their roommate. Why? Because when your early engineer is working late nights to fix a critical bug before the biggest demo in company history, their partner is handling dinner and bedtime alone. When your head of sales is traveling constantly to close early deals, their family is adjusting their schedule to accommodate the demands of an unproven startup.

And when your star hire has a bad day (and trust me, they will have bad days) they will vent. If the support system isn't brought in to the fold and bought in on the opportunity, and instead of joining your company wanted their person to take that higher paying FAANG job with better benefits and more time off, it’s almost guaranteed that will be brought up. And you can’t afford to have grass is greener thoughts of less work, more pay, and happier family life rattling around in your key hire's head.

So the best piece of advice I can give (and founders that work with me will have heard this before) is make sure you’re selling the person or people behind your prospective hire as well. Take their spouse to dinner. Find out what they like. Send a gift for the whole family when you’ve gotten to the offer stage and you're trying to close. It will make a difference, because you can bet most others aren’t.

One portfolio company of ours was recruiting an early engineer to their team. He had competitive offers, and they really wanted to win but couldn’t match on compensation. However, they had learned during their conversations with the candidate that his partner happened to like the ballet, and they were visiting New York that coming weekend. The founders bought the candidate and his partner tickets to a show and had a bottle of champagne waiting for them at their hotel. The candidate signed.

Unsung Heroes of Startups

I have long said that early employees are the unsung heroes of startups (so much so that my co-founder and I started a podcast called Brick by Brick to share some of these amazing stories). They are taking on a huge amount of risk without nearly as much upside, and are the ones who turn the founder vision into reality. They're the ones who will work weekends, take pay cuts, and believe in your mission when the rest of the world is skeptical.

As I’ve said before, the best founders I've seen succeed long-term are the ones who treat hiring as just as critical as product development or customer acquisition. They understand that every great hire makes the next great hire easier, and every bad hire (or missed hire) sets them back months.

So spend the time. Make the calls. Meet the families. Do whatever it takes to convince the right people to join you on the journey. It will be worth it.

This post was prompted both by a number of conversations I’ve had over the years about recruiting early teammates, as well as this post on X by Sanket Shah. Text included in full below:

Wife sent me this text today (I had requested her to tell me about this a couple of days back) and I think everyone can see it:

The Founder’s Wife — by someone who lives the role, silently and fully

When I married him, I knew I wasn’t signing up for a conventional life. He wasn’t the 9-to-5 kind. He was a dreamer. A doer. An entrepreneur with stars in his eyes and a mission in his heart. I was drawn to his fire — the way he spoke about solving problems, building for the future, changing the world. And I knew, in my gut, that loving him would be anything but ordinary.

But what I didn’t fully grasp was how invisible I might feel in the process.

Being married to a founder isn’t like any other marriage. It’s being constantly surrounded by uncertainty, silent tension, and the ever-present hum of a startup in motion. Wins were celebrated publicly — by investors, the team, the world. Losses, however, came home. And they lived with us. On the dining table. In the late-night silences. In the furrowed brows and distracted nods.

I became an uncredited co-traveller on his journey. I carried the weight of his setbacks, absorbed the stress he couldn’t voice, and learned to find pride in a kind of sacrifice that no one really talks about. My emotions, my worries, my longings — they always felt smaller compared to what he was building. So, I minimized them. Quietly.

We never really planned holidays. Life didn’t work like that. Dates became strategy calls. Long drives turned into brainstorming sessions. I’d sit next to him, craving connection — and he’d drift off mid-conversation, lost in thought, deep in the world he was building.

And yet, I stayed. Not out of obligation, but out of belief — in him, in us, in the dream that wasn’t mine but somehow became part of my identity. There’s a constant tug-of-war inside me — to be seen more, heard more — but also to give him the space he needs to fly.

I may not be on the cap table or the pitch deck. But I’m always there — in the quiet corners, the late-night meals, the missed anniversaries, the reassuring nods, the held-back tears. I am his sounding board, his safe space, and his loudest cheerleader.

Because sometimes, love means finding comfort in the background, knowing you’re part of a story far greater than just you.

I believe the sentiment expressed holds true for early employees as well.

If you make recruiting a secondary priority, you’re not going to make it.

As a founder, you have three jobs that really never go away:

1. Set the vision

2. Hire the team

3. Raise the money

The best founders are great at all three. But even if you can paint an amazing vision and convince investors to back you, if you don’t learn how to hire and recruit effectively, you are essentially lighting the money you’ve raised on fire. You just won’t be able to reach escape velocity and venture-scale.

And to be clear, being “good at hiring” does not mean being able to convince the random LinkedIn inbound on a job rec to join the company. It means figuring out your own company’s formula to find the talent that will help catapult your company to success, while also wasting the least amount of the team’s time interviewing the wrong people (wasted time is wasted capital), and offering the right package to close them and retain them.

Now, most of what I said above shouldn’t be controversial. And yet more often than I’d like, I see founders not put in the time and effort to execute on hiring because they get caught in the trap of firefighting the most immediate and urgent problems in front of them.

• “But there's that customer demo next week that we have to nail to lock down the high 5-figure contract, not to mention the huge market validation it provides…”

• “But there’s also prep for an investor pitch with that Seed investor that's been following along with the updates and might want to preempt the round…”

• “But there’s that new onboarding flow we need to implement…”

• “But…”

• “But…”

• “But…”

Starting a hiring process often gets dropped to the bottom of a seemingly endless priority list, or put off entirely. I get it. Who has time to run the search, build the funnel, and run the interview process? You're running a company with fewer than 25 people, and everything feels like a hair-on-fire problem that screams "urgent" in a way that starting a recruiting process simply doesn't.

But at some point you're going to reach a level of scale or hit a time constraint where everything starts falling apart because you don't have the right people in place and they haven't had time to ramp. I've watched brilliant founding teams burn out trying to do everything themselves, simply because they kept pushing recruiting off to "later."

Make Recruiting Non-Negotiable

The solution to creating the rhythm isn't complicated, but it requires discipline: part of everyone's calendar (especially the founders) needs to be recruiting time. Period. You have to think about the roles you need to fill, the Ideal Candidate Profile, and figure out where that person or people is currently spending time.

Just like you wouldn't skip customer meetings or product development, recruiting needs to be treated as a necessary part of company growth, not an optional activity you'll get to "when things slow down."

Make Everyone a Recruiter

Building the top of the funnel can be challenging, particularly in today's hyper-competitive startup environment. But the responsibility for recruiting shouldn't fall only on the founders and recruiters (if there is even a recruiter). The reality is at an early-stage company, everyone's a recruiter.

Your early teammates are the best commercials for your company. They know the culture, they understand the mission, and they can speak authentically about what it's like to work there. More importantly, they likely have networks filled with talented people who might be perfect for your open roles.

I've often had founders ask me if I have any ideas for a founding engineer or someone who can help with early GTM. When I ask whether they've reached out to their own team first, the answer is usually no. That's a mistake.

For every hire you're looking to make, ask your team: "Who else do you know that you think would love to work here?" You might be surprised by the quality of referrals that come back.

You Want Hiring to Compound

Good recruiting decisions compound over time. That first great engineering hire doesn't just solve your immediate technical challenges, they help you interview and attract the next great engineer. The excellent head of marketing you hire doesn't just build your go-to-market engine, they bring their network and help you hire the next layer of marketing talent. Look no further than the Facebook to Instacart to OpenAI talent migration as proof of the benefit of tapping into the right talent networks. There are pre-established quality bars, familiar operating rhythms, and deep trust that will accrue to your company and help you move faster.

But this compound effect only works if you're willing to invest the time upfront to find the right people, rather than just hiring the first qualified candidate who walks through the door so you can “get back to real work."

Trust me, spending an extra week(s) to find the right person for a critical role will save you months of headaches down the road.

The Bottom Line

I know recruiting feels like it's slowing you down when there are a million urgent things demanding your attention. But remember that customer demo that seemed so urgent? You'll nail ten more of those with the right engineer on your team. That investor pitch that's keeping you up at night? You'll close bigger rounds when you have proof that you can attract top talent.

Let the fires burn. Block the time every week. Really list out what you’re looking for from someone entering a role. Find the right people, ideally those who are better than you and will uplevel the whole team. And then work like heck to convince them to join. Your future self and the future business will thank you for it.

Note: Now, the one valid justification for pushing off hiring is when AI can actually help with some of the work that used to require immediate human attention. As Tobi Lutke says, make AI usage reflexive. If you're not instinctively asking "Can AI help with this?" before every hire, you're missing opportunities to buy yourself more time for the recruiting work that still requires your personal attention. But even with AI as an accelerator, you're still building a team, whether it ends up being 5, 50, 500, or 5,000 people. And that means recruiting needs to be part of your regular rhythm.

What is your approach to balancing recruiting with the day-to-day urgency of startup life? I'd love to hear your thoughts. Reply in the comments below.

Thanks Shlok P., Yuichi K., and Arpan P. for feedback and thoughts on this post.