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Hey SF - I’m hanging at 236 Powell Street at art gallery 5pm-530pm. Come say hi?
I'm headed to San Francisco next week. First trip away since my son was born two months ago! My life right now is 3am feedings, a toddler running around, and building in the gaps. Nap time is my new deep work block. So when I say I'm excited to sit at a dinner table and have a
I'm headed to San Francisco next week. First trip away since my son was born two months ago! My life right now is 3am feedings, a toddler running around, and building in the gaps. Nap time is my new deep work block. So when I say I'm excited to sit at a dinner table and have a full conversation with adults about AI agents and startup ideas without anyone throwing food at me, I mean it. I'll be in town for a few days. If you're building something interesting, I'd love to buy you dinner and hear about it. Who wants to hang out in SF?
I literally can't think of a better risk/reward bet right now than building a ChatGPT plugin and getting in front of their 1.2 billion weekly users. As of yesterday, ChatGPT recommends plugins in the middle of conversations. Millions of questions get asked every day with no plugin to recommend. Each one is an empty slot. Facebook apps in 2007. iPhone apps in 2008. TikTok in 2019. Every big platform has a few months where distribution is free, and most people miss it. I saw this firsthand when I lived in SF building venture backed companies. They are sacred times! If I were starting this week: 1. Find a tool or workflow people already Google for or do by hand every week (PDF to Excel, invoice generator, weekly client reports) 2. Build it as a ChatGPT plugin 3. Write the description using the exact phrases people type into ChatGPT 4. Ship 5 of them and see which ones get picked up 5. Double down on the one with the most traction In 12 months these slots will be crowded but right now they're pretty empty. Most people will realize ChatGPT plugins were the biggest free distribution channel of 2026 sometime in 2027.
Stop what you’re doing and build a plugin extension for ChatGPT. We’ve grown over 2000% since the announcement!
My first OBSERVATIONS from Sundar's Gemini 4 Argon announcement: 1. Quantum. Google's quantum researchers gave Argon a key piece of quantum software to shrink, and in minutes it found a version that needs 40% fewer qubits and operations than the best published human solution. Quantum computers are useful ONLY once programs fit on the hardware, so this pulls that date closer from the software side, and it also shortens the time banks and governments have to switch to encryption quantum can't break. 2. Data center memory. A team of Argon agents read Google's server data, found waste, and freed over 300 TiB of memory on their own, with up to 1 PiB expected. If agents can do this everywhere, companies will point them at their cloud bills before buying more servers, and some of the huge data center buildout may turn out to need less hardware than planned. 3. Rewriting old code. Argon agents are converting Google's old C and C++ code into Rust, a safer language, including an 800K- ine operating system kernel. There are PLENTY of companies stay with outdated software vendors only because switching is painful, and once rewriting is cheap, that lock in starts to break! 4. Faster than the engineers. On one video decoder, Argon ran 100s of experiments and ended up 2.7x faster than the version Google's own engineers wrote. Speeding up your slowest code used to take a specialist team, and now it's something you can run overnight and pay for based on the savings. 5. Million-token answers. The most a model could write in one answer went from 64K tokens to 1 million, enough for a whole codebase or a full due diligence report. Obviously, nobody can carefully review that much output, so the bottleneck moves from making things to checking them, and tools that verify AI work become a big market. 6. Two versions of the same model. Vetted security teams get Argon with the cyber safety limits removed, and everyone else gets the restricted one. The best defense goes to big tr...
Lots of discussion out there about our next model(!), so I wanted to give an early look as soon as possible. Introducing Gemini 4 Argon! It shows frontier performance in complex workflows, cyber defense and software engineering. Teams are using it extensively at Google, from
Muse vs Dots vs Grokbot Zuck vs Altman vs Musk. The battle of personal agents for the masses. Who do you think wins?
I found my journal from the year 2000 (I was 11) "in the year 2010 there will be computers everywhere" Nobody knew "everywhere" would mean our phones, cars, doorbells etc The direction was obvious, but the details were impossible to see AI feels exactly like that right now!
How to become a top 1% speaker, in 1 page, whether you're on a panel or anywhere else
more conferences could implement this. so much high value time wasted without thought
I find it fascinating how many people think this is a bad time to start a company. Grok 4.7, GPT-6 Sol/Luna, Opus 5.5, Astra, Gemini 3.8 Live, Muse, Instinct, Jev, Agent APIs etc. That's the last 3 weeks (crazy progress on personal agents/voice AI). Because arbitrage means the same thing trades at 2 prices in 2 markets (and it's your wedge). And usually you have to hunt for those gaps, because they're rare and they close the moment anyone notices. What's different now is that they're opening faster than anyone can build into them! I think this has got to be the greatest time for arbitrage in history.
Are invisible interfaces coming? Google JUST announced Gemini 3.8 Live. It can talk through a task with you, then keep working after the conversation ends. I think 90%+ of vertical SaaS will need a voice front door. By that I mean the way you use the software becomes talking to it, and the typing, clicking, and form filling happens on the other side without you. So a contractor standing on a job site just says what went wrong out loud. And by the time he's back in the truck, the quote is sent, inventory is checked, the CRM is updated, the customer got a text, and anything risky is flagged for him. Kinda the dream, right? The same thing works for nurses, dispatchers, recruiters, brokers, insurance agents etc. The person talks and the agent finishes the admin. Lots of opportunities here to build voice-first businesses (been thinking about this more and more). I think this is how vertical software becomes invisible. Nobody logs in, nobody fills out a form, and nobody learns your interface. You just talk, and the work gets done behind you. This is a glimpse of where SaaS is going. Not fully there yet but it's coming. Invisible interfaces.
We’re introducing Gemini 3.8 Live and 3.8 Live Extended Thinking – our best conversational AI. The models talk, think, and handle tasks in the background without breaking your flow. 🧵
AGENT HARNESSES ARE THE NEW GPT WRAPPERS What exactly is an agent harness? A harness does 4 things: 1. Runs the model in a loop so it keeps working step after step instead of answering once and stopping. 2. Gives it hands to read files, call tools, open portals, and run code. 3. Manages its memory so hour three of a job still knows what happened on hour one. 4. Enforces the rules about what it can touch and when it has to stop and ask a human. WHY IT'S INTERESTING - The market is MEGA. I think about it like a wrapper let you sell software ($800B market) but a harness lets you sell the work ($5T+ market)! - It doesn't depend on any one company's model. The knowledge about the job lives in the harness, so you can run GPT today, Claude next month, an open model like Google Gemma, Qwen, Deepseek etc on your own machine after that, and it keeps working. A wrapper was one model doing everything and a harness is a router. - It gets better the more you use it. See, every correction a human makes becomes a rule the harness keeps, so what you have after 500 jobs is a completely different product than what you had after 5. Wrappers only got better when OpenAI got better. - You can charge for finished work! The harness knows when a job is done, so you can price per claim, per filing, per review, per resolved exception, or per closed month. This helps compete with SaaS! - Most jobs are just the same handful of decisions, repeated, using the same few tools. That's true for most of the 800+ occupations out there, which is why almost all of them could have a harness built for them. Lots of space for startups to be building. -The frontier labs won't come for these. OpenAI is not going to learn how a freight claim gets denied in Rotterdam or which prior auth your specific payer rejects. Those markets are too small for them and the knowledge only exists inside the job. They'll keep making the models better, which just makes your harness better which is cool. - OH, AND rea...
I think building a crowd sourced niche dataset is one of the most UNDERRATED bootstrapped businesses in the AI AGE: (think LevelsFYI, Glassdoor, Zillow etc but for any niche) 1. Your users build it for you by adding their own data (it gets more valuable with every entry) 2. AI agents now need clean, trusted data to make decisions, and they'll pay to query it on repeat 3. Cloudflare (and others!) are building the rails for agents to pay per query, so this becomes real recurring revenue 4. One dataset sells to many buyers at once: consumers, companies, and now agents 5. Charge three ways from the same data: free for contributors, paid for pros, API access for the agents 6. The narrower the niche, the more defensible it gets (you own a corner nobody else has) 7. Frontier models are hungry for data (and are a great customer) 8. The wedge: give a teaser amount of data, then make people add theirs to unlock the rest (ask for data or email) 9. LevelsFYI was brilliant because people will hand over their own salary just to see what everyone else makes (human nature) Big fan of these types of businesses in the AI age. Low risk, high margin, and they get stronger the longer they run!
HOW TO FIX YOUR AI AGENTS (it's called "self-healing agents") If you've run AI agents, you know they BREAK constantly. The FIX is something called a "self healing" agent! A normal agent hits a dead end and just stops, leaving you a half finished mess and that's why output sometimes isn't ideal. BUT, a self-healing one hits the same wall and thinks "okay, that didn't work, let me try another way" HOW TO BUILD SELF-HEALING AGENTS (4 steps): 1. Make it check its own work. After each step, the agent asks "is this what I expected?" instead of assuming it worked and moving ahead. 2. Have it name what broke. Not just "it failed," but which kind: the tool timed out, returned an error, came back empty, or gave a wrong answer. Wrap your tool calls so the error gets passed back to the agent, because it can only fix a failure it can actually see. 3. Match the fix to the failure. Glitch, retry it. Tool down, switch to a backup. Keeps failing, break the task smaller. Anything risky like money or deleting data, stop and ask you. 4. Make it log every fix. It writes down what broke and what worked, so it stops repeating the same mistake in a session, and you get a list of what to fix at the root. That's it. Now, you've got agents that fix themselves.
AI AGENT STARTUP IDEA FOR YOU ($15B market) Yesterday, a friend mailed my newborn a stuffed manatee from Canada, the CUTEST thing, and then I got HIT with $93 in tariffs just to receive it which is more than the manatee cost!! The more I realized this is happening to MILLIONS of people right now, because between the new tariffs and the way cross-border shipping works, everyone's getting surprise fees at the door. A big chunk of those fees are either overcharged, misclassified, or straight up refundable, and nobody has the patience to sit on hold with customs to find out. HOW IT'D BUILD THIS The whole thing starts as an agent that reads your customs and shipping paperwork, the commercial invoice, the HS code they slapped on your package, the duty they charged, and checks it against what you should have actually been charged, because a shocking amount of this stuff gets misclassified by whoever filled out the form in a warehouse. When the agent finds an overcharge, it files the refund claim for you, and you split whatever comes back. Zero risk to the customer, which is the whole reason they'll say yes. HOW I'D GROW THIS I'd make content around the pain they already feel, videos and posts of people reacting to insane import fees on normal stuff, a $93 tariff on a stuffed animal, a $200 fee on a pair of shoes, and every one of those becomes a lead magnet where you drop in "paste your receipt and we'll tell you in 30 seconds if you got overcharged." You can also lean into all the people that hate Trump and his tarriffs, no doubt that’s gonna work. THE WEDGE That free checker is the little wedge product you build. Most people find out they overpaid, you file for them, and now you've got a customer who tells every other person who's ever been burned at the door. HOW TO SCALE Once you've got volume on the consumer side, there’s a huge business in the data. You'll know exactly which shippers, which product categories, and which customs brokers overcharge the mo...
I think we're going to see a lot more creators buy dying public companies (sorry private equity) GoPro is down 98% since IPO. Markiplier (38M subs) is the customer, and knows exactly how to grow it. Creators are the new private equity? Honestly, smart.
JUST IN: YouTuber Markiplier becomes GoPro’s largest individual shareholder after acquiring an 8.5% stake in the company.
Pretty crazy that my company spent $20,987 mostly on AI tokens this month. It's not like someone said hey let's spend $20k a month on AI, it just kinda crept up token by token until one day it was the biggest line on the card. Probably created $200,000+ of value this month.
The question I get most right now is "what should I turn into an AI agent?" Here is the 5 part test I use (works for Claude/Codex/Grokbot etc): 1. It has a repeated trigger, so the same kind of task keeps happening over and over. 2. The inputs are stable, so the information comes in a predictable shape every time. 3. The tools are clear, so there is a defined set of things it can actually go do. 4. There is a measurable finish line, so you can tell when it is done and whether it worked. 5. There is judgment in the middle, so each run is a little different and needs a real decision made in the moment. The first 4 are really just asking "can this be automated at all?" The 5th is the one that matters, because judgment in the middle is what makes it an agent instead of a simple automation. Once you see it this way, you start spotting agent work pretty much everywhere.
The new org chart probably looks something like this: A small layer of humans on top doing strategy, creative, and judgment, with a wide layer of agents underneath running support, sales, research, marketing, ops etc Managing people became managing agents, and managing agents is really just managing context (which is a whole thing millions of people need to learn right now) That shared brain is the actual company now, and the humans and agents just plug into it. Both humans/agents come and go, the context is the thing that compounds and can't be copied. I keep thinking about that.
