partner + builder @645ventures | investing in AI agents, dev tools, and infrastructure | previously @initialized @fcollective @mit | here to help founders win
When the cost of doing something at scale goes to zero, the value of that thing goes to zero too.
AI SDRs will stop working the moment everyone has one. Now the human salesperson has become the premium signal again. Enterprise deals are being closed on calls and text.
The things that don't scale are going to become more valuable as everything else does. Actual presence, carefully nurtured relationships, real conversations, etc. The pendulum always swings back.
SF was over if not for OpenAI and Anthropic!
Before that, it was over if not for Stripe, Uber, Airbnb, Twitter, Salesforce, Visa, Gap... and if you go back a bir further - Levi's, Bank of California, Spreckels Sugar, Wells Fargo, Union Iron Works, Southern Pacific :)
The city gets “saved” by the next boom every time. After the gold rush, there was silver, railroads, shipping, banks, sugar, utilities, Pacific trade, defense, semis, PCs, biotech, enterprise software, the internet, social, mobile, SaaS, fintech, crypto, and AI.
I think that's just how it goes in this town.
sf has tons of free events but they're buried across funcheap, eventbrite, reddit, random instagrams. i'm always looking for something fun to do in sf and i'm sure you are too!
built a map that pulls them all into one place - comedy, workshops, art openings, free food, pop-ups. updates daily... check it out! 🧡
https://t.co/j4D8U0HWfc
It’s wild how Meta - a company going all-in on AI - somehow missed the memo on how AI can generate images and videos that renders “take a selfie of yourself” verifications utterly useless
So now Instagram accounts hacked at scale. 2FA also fully bypassed - by Meta’s own design
Anthropic headed to IPO with craziest revenue ramp in history:
2021: Founded
2022: $10 million
2023: $100 million
2024: $1 Billion
2025: $9 Billion run-rate
January 2026: $13 Billion run-rate
February 2026: $19 Billion run-rate
March 2026: $30 Billion run-rate
April 2026: $44 Billion run-rate
May 2026: $47 Billion run-rate
I don’t think any of you understand what is about to happen in the market. We are about to live through the craziest five year run in technocapital history. God help us all. I pray that when Judgement comes He can see all that we did to ensure efficient price discovery.
someone hit me up about the new "claude dynamic workflows" feature, claiming "see, multi-agent works"
But really, the launch of this feature proves the exact point that I made back in June of 2025, along with @walden_yan, @tobi, @karpathy, and many others:
Deterministic workflows orchestrating small agent loops beats non-deterministic multi-agent or "agent soup" systems every dang time
everything is context engineering
If you work in the software industry and have time to read only one long-form post today, read this one.
If you have time to read two, read this one twice.
Highly #recommend
tl;dr: Stay off the yellow brick road that the frontier model companies are racing down. There is plenty of opportunity to solve hard problems elsewhere. Focus on areas where you can build the system of work (workflows), capture compounding, non-public data and deliver deterministic outcomes that customers need.
Insane stat of the day: California almonds use roughly 3–5.5 million acre-feet of water per year, depending on methodology.
That's ~4-7x more water than all data centers in North America used combined in 2025.
Building in Public was the playbook. Not anymore.
If you're a founder, don't give competitors a sniff of what you're working on until you're ready for showtime.
No benefit anymore to building in public. People are too busy to care what you're doing & they'll happily copy you.
Brendan Hopper, Matt Beane and I have a thesis, one that I've been sharing around lately, and we want CEOs and boards to hear it.
Before I get to the thesis, let's revisit Clayton Christensen's Innovator's Dilemma (ID), the theory he developed at HBS to explain why big companies often get eaten by upstarts during technology shifts.
In short, the ID says incumbents serve their best customers so well, and tune themselves so ruthlessly for doing exactly what they do today, that they can't chase the disruptor tech coming up from below until it's too late.
The classic solution to the Innovator's Dilemma is to create a "bubble" in your company. You carve out an innovation team with a budget and mandate, as unfettered as practical by the parent organization. This is to combat the 2-level trap presented by the dilemma.
The economic trap is Christensen's original point: a disruptive technology can't justify itself under your existing P&L, because it serves smaller or weirder customers at margins your real business would never accept.
The governance trap is what gets piled on top once you're big: SOC2, FedRAMP, etc. mean every new idea has to clear a lot of process before it can move. The bubble is intended to escape both at once, with its own economics and permission slips.
The standard innovation "bubble" solution famously doesn't work very well. You may solve the problem inside your bubble, but you often can't roll it out to the rest of your company for the original reasons. Everyone is focused on doing their current stuff, and nobody has time for a major change.
Our thesis is that there is an entirely different way out of the dilemma this time around. No bubble needed, as long as you follow a simple rule. That rule is, let your people play. Give them back any time they earn from automating their jobs with AI. Then incentivize them to use that time to improve the company's processes.
When you see an engineering team announce a 40% productivity boost from adopting AI — a number that's been showing up in plenty of LinkedIn posts lately — your first reaction as a CEO or manager is probably to say, that's awesome, we can do more work now! Or you might simply expect to see 40% more output from the team.
Either way, you have just asked them to spend their extra time building faster horses (your current business) instead of letting them go figure out what a car would look like for your company. They gained some productivity from AI, which could have been your ticket out of the Dilemma, and you immediately slurped it back for your existing business.
This will get your company killed in the medium to long haul, because your company tomorrow will look almost nothing like it does today. Conway's Law says your software and your org chart mirror each other; as AI rewrites how you build software, the org has to shift to match. But if you're stealing the hours back saved by your employees, then you're not letting your org pivot naturally in the direction it needs to shift.
@RealGeneKim and I saw this in person at @arkanalabs a few weeks back. As long as your people know they'll be recognized and rewarded if they improve the company's processes — public credit for cross-team workflow wins, promotion criteria that actually count process improvements, managers who treat freed-up hours as a feature rather than a budget line — then they will use their "play time" to seek out other teams, and start pivoting you to becoming AI-native. This way it can unfold in whatever bespoke way is most natural to your company, rather than in some ivory-tower research bubble. For every company, the way it unfolds will be a bit different.
I think of this approach, of giving the time back to the humans who automate parts of their jobs with AI, as the new solution to the Innovator's Dilemma. The old bubble solution was to separate a bunch of people from their regular jobs, and try to give them the freedom to solve the problem in isolation.
In contrast, by giving your regular employees their hours back, the innovation bubble is still there, but it's now dispersed across the company, as lots of very tiny bubbles: one bubble per person who has liberated some hours.
If you've ever read Slack by DeMarco and Lister, a great book from back in the 90s, then our thesis should resonate. What companies need is to empower their own employees, the ones who actually work together (even across departments)--the ones who know how the business works--to shift the company in the new directions together. Gradually, but with intentionality.
You still have the frankly awful problem of token budgets. For every employee you upskill into baseline AI literacy (which I'd define loosely as using coding agents throughout the workday), you've added a non-trivial opex spend — for the heaviest agentic users it can run into five figures a year. I won't sugar-coat it; you need to find that money somehow. I don't have a magic solution, but I'm very happy that other models are catching up to Claude, because they're becoming good enough for real work now.
But token budgets alone aren't enough. To live through the Innovator's Dilemma this time around, your employees need a time budget, too. Give it to the ones who earn it using AI, then incentivize them properly, and I think you're headed in roughly the right direction.
Thank you for coming to my TED tweet.