as bad as things have gotten in the past 4 days, they are going to get a lot worse before they get better. security leaders, never let a crisis go to waste: please go to your boards and ask for help right now. not for ai, for the basics. (we need to hold on for ~18 months.)

I highly recommend cloudflare's security audit skill: github.com/cloudflare/securi… Run it on all your software. Run it with the free models. Use it even if you used a model to audit something - it will find much more things. Works in all agent harnesses and is model independent.

I spent 48 hours in SF hanging out with billionaires, data labs and AI founders and execs running $1B to $100B companies. My observations: 1. Sooo MANY stories of data brokers making like $2M a WEEK selling company data to labs. I can't tell if it's the beginning or a bubble, and I kept wondering which niches are left. Digging into it actively. 2. At dinner, someone asked the table, "If a new model drops next month, does your company get better or worse?" HALF the table went quiet! I think that's the best question to ask about any AI startup right now. 3. The bar people talk about now is hitting $1B in revenue in 12 months (I guess that's the new unicorn?). What I didn't hear much about is retention. AI revenue can come in fast and leave fast, and I think we're going to see a lot of stories of AI companies with huge revenue and terrible retention. 4. It's pretty clear we're living through the reinvention of the computer. The model is the CPU, the harness is the operating system, and skills and plugins are the apps. Thinking about it that way makes it easier to see where the whitespace is. 5. We're maybe 12 months from an agent that can watch you work for a week and then do your job without any instructions. The screen recording plus agent memory plus local model combination makes this possible right now. 6. Agent harnesses feel like the new GPT wrappers, in a good way, especially vertical ones. The best teams I talked to treat the model as swappable. One founder walked me through routing different models to different jobs: one for taste and visuals, a cheaper one for the everyday stuff, another for text. They use prompts they can move across models over fine-tuning, and A/B test the output on what users actually do with it: do they edit it, export it, share it? A vertical harness is basically four things: the connectors for that industry's data, evals written by people who know the work, rules for what the agent can and can't touch, and a clean screen for a human to review. The model is maybe 20% of it. 7. There's a lot of reverse engineering going on/cloning going on more than I've ever seen. People are decompiling software and rebuilding it with agents, and someone showed a suite of like 10 apps that are worth $5B+ each all that he cloned open source. Me and everyone are still thinking through what it means when software gets this easy to copy. 8. My guess is the value moves to data. If the software can be rebuilt quickly, what's worth paying for in a legacy SaaS company is the years of customer data and workflows inside it. Some SaaS companies are secretly data companies. Gets me thinking about how do you truly value data for this saas companies? Like if we were buying these dying saas companies at 2x ARR before (as example), maybe there is a better metric. Idk, just thinking out loud here. 9. It feels like a good chunk of legacy software won't make it to the agentic era, especially anything built around people clicking through a lot of screens. 10. Every company I talked to wants to pipe its internal data into one place and expose it to agents through MCP. Then they look at the data and realize it's a mess: five versions of the same customer, old Slack channels, PDFs nobody can search. Cleaning that up feels like a big consulting opportunity! 11. A lot of founders are building the basic building blocks for agents: APIs, data layers and tools. Some of the companies I saw barely have a UI because the main user is an agent. I really believe the startups that build primitives to this agentic era will do extremely well. Building blocks is the best way to think about it. 12. Labs can get plenty of training data, but it's harder to get real examples of agents failing inside companies. Whoever has those logs has something valuable. 13. Someone running a big consumer company told me the next fight is over memory. The model that remembers the most about you wins, and the smartest model matters less than people think. 14. Physical AI came up a lot. Astra I think was the first model that got people into AI can actually do CAD, and I think a lot of people are thinking what does vibe manufacturing really look like. The line I keep thinking about came from a robotics founder: the hardest problems in AI are deployment problems now, not research problems. Their robots work on their own, call a human when they get stuck, and every one of those calls becomes training data. 15. Cybersecurity companies are having a moment and are actually cool companies to build now, especially the ones that clean up after a breach. Every agent with access to your systems is a new door into your company, and a lot of those doors were left open. 16. Some startups are worth more dead than alive now. A shutdown company with 5 years of Slack, email and code can get paid for licensing all of it. I wouldn't be surprised if founders start factoring that into when they shut down. 17. People are starting to talk about monetizing the agent web. It feels really early, but when the most popular user of the internet is an agent, what startups should you be building? 18. I think agent insurance is coming. Once an agent makes an expensive mistake, insurers will want audits before they cover anyone. 19. Several people said the hire they want most is someone with taste who can write evals. The models are getting good at generating ideas, so the hard part is judging which ones are good. 20. New trend I observed: startup raises VC, uses venture dollars to become a creator, startup fails, founder falls back on being a full-time creator and incubates other products bootstrapped. 21. Getting SIGNIFICANT distribution is HARD right now. Founders are sponsoring buses, buying billboards like crazy and throwing parties with famous DJs to get noticed. Kinda feels dotcom era in that sense. Attention is what's scarce! The growth guy going viral sharing his UGC strategy from Wispr Flow is a good example. It's the sauce everyone wants, and I truly believe there are probably only 50 people on the planet who know how to scale these types of businesses efficiently in this era. Always good to get that dose of SF. I felt sooo lucky to have such an incredible trip during such an incredible time in building businesses. Surreal in so many ways. Happy to be home and locked in. Until next time!

we raised $32M and i want to be honest about what that money did and didnt change what it did was buy us the ability to not be desperate and that turned out to be the whole point desperate companies make bad decisions they take the wrong customer because they need the logo they ship a half-complete feature because they need the launch asap they say yes to a partnership that reshapes the product roadmap because they need the runway the money didnt make us smarter or anything like that it just removed the pressure that makes smart people act dumb thats why were profitable, growing 3x a year, and under no pressure to exit on someone elses timeline we can keep this exact growth rate for quite a while too and that freedom is worth more than any number in the bank heres what i tell founders now dont raise money to grow faster raise it so fear stops making your decisions for you the best thing capital can buy is the ability to be patient almost nobody uses it that way

spent some time reverse engineering how cloudflare became the #1 chatgpt recommended infrastructure platform 37% visibility score. 3x ahead of AWS across 34 queries. >they have a learning center with 300+ educational pages answering questions like "what is a CDN" and "how does DDoS protection work" before ever mentioning their product >they compete in 6 product categories at once and have dedicated content for each one >they run 4+ innovation weeks per year (birthday week, developer week, security week, speed week) each generating dozens of indexed blog posts >they win every cost query on chatgpt. "cheapest CDN" "s3 with no egress fees" "aws s3 alternatives". cited #1 on all three >they show up on both chatgpt AND gemini. 9 citations on chatgpt, 7 on gemini. this is possible for u to do. will expand on how they did it in this thread 👇 if u want us to do a deep audit on your company for free just comment "audit" 🫶

We’ve raised $34M, led by Roo Capital and Grand Ventures. 18 months ago we started Comp AI with one idea: agents will be responsible for compliance busy-work. Today, 1000+ companies like @UseCorgi, @opencode and @dubdotco trust us to get them audit-ready.

Too many AI personal assistants, too little time to assess all of them. Nice work here: assistantbenchmark.com

Workers now enables Node.js compatibility by default, supports applications up to 64 mebibytes, and adds a URL-based module registry with import.meta, lazy compilation, shared code caches, and clearer errors. cfl.re/4ymgiqz

Since I'm seeing Cloudflare trending... Reminding everyone that OpenSEO runs entirely on Cloudflare (+ Planetscale for our hosted product). We use tons of their products like Durable Objects, KV, R2, D1, and their Agent stuff. This was all $5/month until very recently github.com/every-app/open-se…

Met a German founder this week and asked him if all the stories one reads about the challenges of startups in Germany are exaggerated. "No, they're understated." Proceeded to describe spending a full day having a 90-page investment contract read to him (mandatory under German law; § 13 BeurkG) by a notary that then charged €30,000. That was for his first company. His second company, needless to say, was not incorporated in Germany.