The Computomatix Times

We're excited to release OpenInstinct

Instinct but self-hostable, open source and supports every model. You control the code, data and passwords

Deploy on Vercel and never use the internet with your fingers again

github.com/Merit-Systems/OpenInstinct

I made some headless tools for your agents

hdls.tools are little saas apps with no UI

1. URL Shortener
2. Pastebin
3. An email client (grab your handle now)
4. Self reminder (email yourself)
5. File sharing - upload and get a URL

Sign up or host it yourself - its open source and runs on @CloudflareDev

I built a shopping agent inside iMessage. Open sourcing the code: github.com/gil--/ucp-agent-imessage

1. Send a msg or photo.
2. It searches Shopify’s global catalog.
3. Builds one cart per merchant.
4. Connects Shop identity w/ budget.
5. No cc details exposed.

Why Shopify? Shop identity already covers hundreds of millions of buyers.
One protocol (UCP), every merchant. Millions of products. No scraping or “computer use”is necessary. 💚

Sachin and Adam are making my favorite short documentaries about technology companies.

This one, about Fortell (I’m an investor), is especially interesting.

This is the sort of company that I hope AI enables in as many industries as possible.

Fortell has combined AI technology (a custom chip and software) with good old-fashioned extraordinary customer service to make living with hearing loss much easier. Many people I’ve seen try the demo have cried at the impact and quality. So cool.

Check out Sachin and Adam’s other videos too. All excellent.

ideas ki kami nahi honi chahiye

trywallfacer.com

100k+ ads from top DTC brands in India & US

all for free

hooks, timeline, format, offer everything analyzed by frontier AI

I’m automating as much office work as I can at my Plumbing company using Grok @bot

Here are the agents I’ve “hired” and a little bit of how I used them all in our company

Thread 🧵

Whoa, Cloudflare is launching AI visibility reporting (for free I believe). For companies providing those services and tracking, this is a huge heads-up. You can sign up for the beta today ('Register interest'). See below:

"To evaluate how an AI model perceives your market presence, we build a benchmark across each industry and category before scoring a specific site. We query AI assistants with likely prompts in that category — without specifying your brand — and record which sites are cited, where they appear, and how prominently they feature."

"Alongside the answers, an AI Operator Activity shows the real crawl and referral traffic on your site, per operator (OpenAI, Google, and so on): who reads your content, who sends visitors back, and the errors they hit on the way (403 blocked, 404 dead link)."
blog.cloudflare.com/aeo/

so you want to build an AI stylist

Jack, who launched Profit AI in December, says his $147K revenue split came from $30K/month on the app and almost $40K/month in services, all in five months.

"I built a profit analytics and marketing automation app for Shopify called Profit AI, which has made a total of $147,000 since launch in December, and is currently at 30K MRR for the app, and just under 40K MRR for services."

"We had no customers for the first couple of weeks, just a handful of brands that I knew that were beta testing the app and getting free access, and yeah, today I'm excited to share more about how I took it from zero to where it is now."

THE LABS WON'T WIN THE APP LAYER
@mignano (Mike Mignano), General Partner, Union Square Ventures, interviewed by @HarryStebbings (@20VC)

Summary: Mignano's argument is that the AI infrastructure buildout is largely finished, and value now shifts to the application layer, the way broadband once gave way to internet apps. He thinks the frontier labs cannot capture that layer, because markets rarely crown a single winner and specialized startups keep beating incumbents at the hard, regulated, context-rich problems. The takeaway for builders: move first, stay mission-driven, and spend tokens like the advantage they are.

1. The App Layer's Turn. The infrastructure is built, and now the applications get built on top of it. Mignano compares this moment to the early internet, when fiber and broadband were laid down and then an application layer arrived to use them. Trillions in value came from the labs' buildout, but the next wave is software, and there will be so much of it that you cannot place a bet unless you know exactly what you are looking for. That is the whole case for a thesis-driven fund over a consensus-driven one.

2. Obliterate, Don't Automate. USV backs companies that reinvent how something works, not ones that make an existing process incrementally faster. The example is Doctronic, which USV seeded on the idea of putting an AI doctor in everyone's pocket rather than helping practices process insurance claims. Automating a workflow usually means selling to a middleman and making incumbents a bit faster. Reinventing the model is where the enormous outcomes live.

3. Token Maxxing. If Mignano ran a startup today, he would still pound the table to maximize token spend on the things that matter, especially coding. A great engineer will pick the startup that says spend whatever you need on frontier models over an incumbent that hands them a constrained budget. Big companies like Salesforce, Microsoft, Meta, and Uber have to rein in spend because they carry tens of thousands of employees; a startup does not. Token spend is an advantage, and a small team should use every dollar of it against a giant.

4. The 3.8% Question. The entire bull case for Anthropic comes down to what share of developer salaries gets spent on tokens. Marc Benioff spent $300 million with Anthropic on his dev team, which works out to roughly 3.8% of those salaries. If that figure climbs toward 20% or 100%, Anthropic is wildly undervalued and its exponential revenue holds; if it stalls or spend migrates to open models, the story changes completely. One ratio decides whether the most valuable private company in the world is cheap or expensive.

5. Frontier Only For Code. Roughly 80% of non-coding enterprise tasks can run on models that are nowhere near the frontier. Summarization, drafting docs, and routine operations do not need the best model; coding does. That split creates room for a routing layer that sends each job to the model with the best price-to-capability fit. Open-source models are catching up fast enough that the frontier is only worth paying for when the work demands it.

6. The Rebel Alliance. Mignano is planting USV's flag in open-weight models, open harnesses, distributed compute, and human-aligned agents. Teams go where the incentives are, and as open options become genuinely competitive, smart teams drift toward them. China's open-source ecosystem is evolving at a startling rate, which pulls even more talent into the open camp. Publishing a thesis like this is a bat signal that tells the right founders who to call.

7. Who Is Your Agent Working For. As people hand agents their credit cards, their messages, and their agency, they will start asking whose incentives the agent actually serves. A lab's model is built to make the lab's model smarter, and a user may want a harness aligned with their own goals instead. Not everyone has to care about this for it to matter; enough people caring keeps a few good actors honest and holds the rest in check. Alignment with the user turns into a product feature and a real reason to pick one harness over another.

8. The 30% Rule. Markets almost never hand one company the whole thing; the winner usually takes about 30% and leaves 70% up for grabs. Coding assistants prove it, with Cursor, Lovable at $500 million in revenue, and Cognition all thriving at once. Anthropic put a whole team on design to go at Figma, and Figma still does billions with a trusted brand intact. Mignano changed his mind on this in the past year: even the biggest labs cannot do everything, just as Google and Apple never did.

9. The Context Moat. The durable advantage in AI products is the context they build up once they are inside an organization. Granola wins by doing one thing, meeting notes, and doing it best, which gets its foot in the enterprise door without asking anyone to rip out Gmail or Docs. Once a company's history of notes lives in the product, nobody wants to give that context up. Being first and staying focused is how a startup builds a moat that even Microsoft's bundling struggles to pry loose.

10. The Energy Floor. No matter which model wins, intelligence runs on power, so USV has been betting on energy since 2021. The portfolio includes Radiant's factory-line small nuclear reactors, Fuse, and Rune's micro data centers that sit next to wind farms to solve energy portability. These bets are capital-intensive at scale but cheap in the earliest days, when a team is running science experiments before anyone else is paying attention. The edge of energy innovation is exactly where a venture investor should place early bets.

11. Founder Over Market Over Product. Mignano used to rank product first; now he ranks founder, then market, then product. Early startups almost always pivot, so what matters most is whether the founder is resilient, can execute, and can adapt. The trait he underweighted is communication, which touches recruiting, fundraising, product vision, and storytelling to the market. A founder who cannot communicate cannot align a team or raise the capital to build.

12. Price As A Litmus Test. Fred Wilson's rule is never pass on price, and Mignano now uses price as a test of his own conviction. For the best founders, you would pay double and still feel good about it in hindsight. His hardest lesson as a former operator was to stop projecting his own plan onto founders, because even when your plan is right, it is their company and betting on your version is how you misjudge the team. The discipline is to trust the founder's judgment, and to let price tell you how much you actually believe.

This app sells grandma stickers and makes $100K/mo

Under 5000 downloads last month

The whole trick is one price:
- $6.99 a week, not a month
- Looks cheaper than $24.99/month
- People tap it, pay $363 a year

We obsess over the perfect app

The winners obsess over distribution

One guy built a wedding camera app in a month and it now makes him over $1,000,000 a year.

No team, no investors, no marketing budget. 100,000 downloads in the first month. Zero dollars on ads.

He did not bolt marketing onto the product. He made using the product the marketing.

You cannot use the app alone. The host has to pull every guest into it. One wedding is not one user. It is 200 people scanning the same code in one evening.

The guest liked it at someone else's wedding. A month later he throws his own event and brings his own crowd. The loop spins for free.

It does not look like an ad. To the guest it is a gift. So they install it gladly.

$2 to $50 subscriptions. 5% pay. That is $100,000 a month.

He did not win on budget. He sewed the growth into the product itself.

Could you build the loop, or is it just luck?

this is everything you should know before building an app.

i’m not even joking, save this.

Jack, who built a $30K/month Shopify app with AI (and can't code), says most of his growth came from word of mouth he hasn't even hard launched yet:

"We have 43 uninstalled and 47 installed. We've made $147,000 to date. We have 122 users of the app right now."

"Most of our growth came from like word of mouth. We haven't hard launched in marketing yet at all, but soon we're going to do a big launch."

"Paid plan used to be $5,000 a month, but we only had a couple of takers… so we dropped it down to $800 a month."

The Invisible Metric in Startup Building: "Founder Form"

When Messi goes five matches without scoring a goal, or Virat Kohli goes through a dry spell, the sporting world doesn’t assume they’ve suddenly forgotten how to play. We don't demand they be permanently benched or declare their career over.

Instead, we use a very specific word: Form.

We recognise that sports require immense psychological, emotional, and physical intensity. "Form" fluctuates. It has peaks, valleys, slumps, and flow states.

Yet, in the hyper-rational, metric-driven world of startups, we treat founders like machines. We expect them to ingest capital and seamlessly produce flawless strategic execution 365 days a year. If a quarter misses expectations, a product launch bombs, or a key hire walks out, the immediate reaction from boards, markets, and sometimes even fellow co-founders is panic, blame, or a sudden loss of faith.

Over the last 19 years as an entrepreneur and through supporting hundreds of founders in their journeys, I’ve realised one undeniable truth: Founder Form is real. And ignoring it can destroy perfectly good startups.

The Anatomy of the Two States: The Slump vs. The Flow
Building a company demands an elite athlete's intensity. Because it relies heavily on human judgment under extreme uncertainty, founders inevitably move through distinct cycles of form:

When you are in "Bad Form" (The Slump): Every strategic bet feels slightly off. You make a hiring mistake, a key client churns, your pitches don’t quite click, and your decision-making feels sluggish or over-analyzed. You are working just as hard - often harder, out of sheer desperation - but your timing is gone.

When you are in "Good Form" (The Flow State): Everything you touch turns to gold. You make a gut-call on a product pivot and it works flawlessly. A casual coffee meeting scales into a massive strategic partnership. Investor meetings go super smoothly. Your energy is infectious, and the team rallies without effort.

When you are in a slump, it feels like nothing will ever work again. When you are in flow, it feels like you can never fail. Both illusions are dangerous, but the slump is where companies break.

The Danger of Asymmetry in Co-Founder Pairs
The ultimate test of a co-founder relationship isn't how you celebrate wins together; it’s how you handle a divergence in form.

In a multi-founder setup, it is incredibly rare for all partners to be in peak form simultaneously. The danger arises when Co-Founder A is in a legendary flow state, while Co-Founder B is grinding through a deep slump.
If they don't understand the concept of "form," this asymmetry breeds deep resentment. Co-Founder A starts thinking, “I’m carrying the entire weight of this company.” Co-Founder B, already drowning in self-doubt, feels isolated, judged, and increasingly anxious - which only prolongs the slump.

Great co-founder relationships survive because they view performance through the lens of a team sport. When your partner’s timing is off, you don't call them incompetent. You step up, cover the field, take the heavy shots, and give them the breathing room to find their rhythm again. You do it gladly, knowing that next quarter, the roles might be reversed.

A Message to Investors: Stop Managing to the Daily Scorecard
To the investor community: when a founder is in a slump, adding institutional pressure or questioning their fundamental capability is the equivalent of a manager screaming at a struggling athlete from the sidelines. It doesn't fix their footwork; it merely tightens their grip on the bat.

Seasoned investors back the person, understanding that form is temporary, class is permanent.

If a founder who has previously delivered high-quality execution hits a wall, the goal shouldn't be to micro-manage the metrics. The goal should be to help them remove the noise so they can find their baseline.

The Founder’s Playbook for Regaining Your Form
If you are a builder currently grinding through a slump, remember how elite athletes get back into the runs:

Go Back to Basics: When a batsman loses form, they spend hours in the nets focusing on basic footwork, not hitting sixes. Stop trying to solve the entire macro crisis today. Focus on small, undeniable execution wins. Go talk to three customers. Fix one internal bottleneck. Rebuild your momentum incrementally. Confidence will grow with action, shrink further with idleness.

Manage the Fatigue: Founders tend to respond to a slump by doubling down on work, leading straight to burnout. But a chaotic mind cannot produce elite execution. Step back, rest, and disconnect briefly to regain perspective.

Trust the System: Accept that market forces and luck play a massive role in early-stage startups. If the core capability is there and you keep showing up to the crease with clean mechanics, the flow state will return.

Startups are a game of endurance. We can’t expect builders to be flawless algorithms, and we must support them like the elite psychological athletes they are.

Give your co-founders and yourself the grace to find form again. It’s just a matter of time before they find it.

Launching Raaga V1 by Vakyam AI.

Natural, expressive speech for Indian languages.

Frontier-level quality at ₹0.75 per 1K characters (~per min).

Try it now on our playground.

Every product company is facing the same dilemma right now: Do you try to be the agent your users open every day, or do you accept they already live in Claude/Codex and power that agent instead?

Wrote about how to think through it and what building an MCP business might entail

just dropped on @starter_story

flamme: $0 → $10K mrr. 250K downloads. 50M views. zero paid.

one tiktok farming system, 15 min on tape.

→ vsc framework (viral, scalable, convertible)
→ the ugly tracker we run across 50+ accounts
→ why most viral videos don't convert

video link below (vsc tracker template attached) 🫡

still surprised by how much money plant identifier apps can make

the first one on this list is making $9,000,000 a MONTH

Two of our worst VC stories:

1. A Sequoia partner passed on Cloudflare because he didn’t think a woman could lead a security infrastructure company. Seriously. 🙄

2. I got introduced to @pmarca. Meeting got scheduled for a Monday, which should have been a clue. I thought it was just a casual meeting. He thought it was a pitch and brought the whole @a16z partnership team. Hilarity ensued. 🤪 At one point one of them said: “You don’t seem very prepared.” Which was true because I wasn’t. I framed the rejection letter they sent.

Today, I’m launching my newco, NavigateAI. We are short hundreds of thousands of skilled workers and we're on a mission to give every field worker an AI copilot, so they can build faster and better when we need it most. navigate.ai/blog/2026-05-26-launching-navigateai

This girl is insane. 4 different apps doing $150K/month each! 🥶

If I wanted to quit my job & use AI to get rich by Summer, here's exactly what I'd do:

1. Start a faceless Instagram page before the week is over. Not next month. Not after you "research more." This week.

My 30+ observations on the greatest opportunities in AI agents right now:

And some ideas that are keeping me up at night.

1. The new buyer on the internet is an AI agent. Imagine billions of new customers showing up with money to spend but they only shop via MCP. That's what's happening. No MCP server means you're invisible to the fastest growing buyer on the internet.

2. Every franchise system in America (30,000+) needs an agent layer and none of them have one. One founder per franchise vertical. That's 30,000 businesses waiting.

3. Everyone said "distribution is the only moat" a year ago. Now I'd add that the only moat is distribution plus memory. The company that has your audience AND your agent's accumulated context is impossible to leave.

4. Consumer mobile is more interesting than it's been since 2012. Apps can finally DO things for you instead of showing you things. The next wave of $100M apps are being built right now.

5. The most interesting startup nobody has built is an agent marketplace where you rent access to someone else's trained agent. A recruiter spent 6 months training a sourcing agent on healthcare hiring. That agent is worth renting to every other healthcare recruiter on earth. The agent itself becomes the product.

6. A sorta strange phenomenon that's happening right now is agents are developing preferences. Give the same agent the same task 100 times and it starts developing patterns in how it approaches it. Nobody is studying this yet. But the agents that develop good patterns are worth more than the ones that don't. That's a new kind of asset.

7. Dead internet theory is about to become dead SaaS theory. Half the apps you use will quietly replace their support team, their onboarding team, and their content team with agents. You won't notice for months. Then you'll realize you haven't talked to a human at that company in a year.

8. The most valuable data in the world right now is sitting in the support tickets of small or mid tier SaaS companies. Every ticket is a customer telling you exactly what to build next. Mine this.

9. The most interesting pricing problem nobody has solved is how do you price a product when your costs change every time OpenAI or Anthropic updates their model pricing? Your margins can swing 40% overnight based on a decision made in San Francisco. The company that builds dynamic pricing infrastructure for agent-based businesses solves a problem every AI company has.

10. The best AI products feel like they're reading your mind. The worst ones feel like filling out a form with extra steps.

11. An interesting arbitrage I've noticed lately is hiring a human VA for $20/hour to supervise an AI agent that does $200/hour work. The human just checks the output.

12. The managed AI agent business is becoming the new agency model. $5k/month per client. You build it, run it, maintain it. The client gets a digital employee they never have to think about. This will be a $50 B+ category.

13. The first "shadow agent" scandals are about to drop. Employees running personal agents on company infrastructure without telling anyone. Using company API keys. Agents accessing internal docs. IT departments have little visibility into this right now. Lots of opportunity to build companies here. Definitely a painkiller not a vitamin type of business.

14. Right now there are probably millions of agents running on autopilot that their creators forgot about. Still burning tokens. Still sending emails. Still scraping websites. Still costing money. The "find and kill your zombie agents" tool is a product that writes itself.

15. Companies are starting to hire based on someone's agent portfolio instead of their resume. "Show me 3 agents you built that are running right now." It's REALLY early but it's starting.

16. Your Slack archive is a product. Every company's internal Slack has thousands of messages explaining how they actually do things. The company that lets you point an agent at your Slack history and auto-generate SOPs and agents from it will be enormous.

17. We're watching the cost of intelligence fall faster than the cost of distribution. Which means distribution is now the expensive thing.

18. The most underrated asset a human can have in 2026: the ability to sit in a room with another human, make eye contact, and have a real conversation. As AI handles more of the transactional stuff, the humans who can do the relational stuff become disproportionately valuable. The soft skills people used to dismiss as fluffy are becoming the hard skills. The hard skills people spent decades acquiring are becoming the soft ones.

19. There are MANY huge companies to be built around the fact that most people's agents are running on their personal laptops which they also use to browse the internet, check email, and download random files. The attack surface is enormous. One compromised Chrome extension and your agent's API keys, customer data, and workflows are exposed.

20. There's a new type of burnout forming that doesn't have a name. It's not from working too hard. It's from context switching between human work and agent work 50 times a day. Reviewing agent output, correcting it, approving it, reviewing again. The mental load of supervising agents is different from the mental load of doing the work yourself. Some founders are telling me they were less tired when they did everything manually because at least the cognitive pattern was consistent.

21. The cheapest form of market research: search "[your industry] spreadsheet template" on Google. Whatever people are tracking manually is your product.

22. Half the YC companies pivoted within 8 weeks of demo day. Not because they failed. Because agents let them test 5 ideas in the time it used to take to test one. The concept of "committing to an idea" is dissolving. Serial pivoting is becoming the default because 1) AI lets you move fast 2) the world is moving fast.

23. The loneliest job in tech right now is being the only person at your company who understands what the agents are doing. You can't explain it to your boss. You can't hand it off to a colleague. If you leave, everything breaks. You've become a single point of failure for an entire automated system. That person needs a title, a team, and a backup plan. Most companies haven't figured this out yet.

24. Your browser history is the most valuable training data you own and you're giving it away for free. Every site you visit, every product you research, every competitor you study, every pricing page you screenshot. That behavioral data, structured and fed to an agent, would make it understand your business better than any onboarding call. The company that lets you turn your browser history into agent context builds something nobody can replicate.

25. Everyone is building AI wrappers. Nobody is building AI unwrappers. The tool that takes an AI-generated document and tells you which parts a human wrote and which parts were generated.

26. Stripe just became the most important company in the agent economy and they barely had to do anything. Every agent that sells something needs Stripe. Every agent that buys something needs Stripe. They're the payment rail for the entire agentic internet by default.

27. The most undervalued API in the world right now is the US Postal Service address verification API. It's practically free. Every local business lead gen agent needs it. Every real estate agent needs it. Every direct mail agent needs it. Boring government infrastructure is quietly becoming the backbone of agent-native businesses.

28. The concept of "business hours" is for humans. Your agent closed a deal in Tokyo at 3am, processed the payment, sent the onboarding email, and updated the CRM before your alarm went off.

29. What happens when agents start recommending other agents? Your research agent finds that a competitor's sales agent is better and suggests you switch. Agent referral networks are forming organically. The first agent affiliate program is probably 6 months away.

30. Cal dotcom closed their source code. That's the canary. When open source companies start closing up, it means agents were cloning their product too easily. Every open source company is quietly asking the same question right now.

31. "AI for pet groomers" sounds like a joke and that's exactly why it will work. 150,000 of them in America. Zero tech. All scheduling by phone or IG DMs. The joke ideas always win.

32. The thing that will seem most obvious in hindsight: we spent 2025-2026 arguing about which model is best while the entire value was in the orchestration layer. The model is the CPU. Nobody buys a computer based on the CPU anymore. They buy it based on what they can do with it. Makes so much sense in hindsight. What else will be obvious in hindsight?

I'll share more notes soon.

I can't sleep with all that's going on. Maybe you too.

What an incredible time to be building.

We just rebuilt ixigo from the ground-up to become AI-native. Not a redesign. Not an update. A completely new way to experience travel. Tara, our AI agent understands you, assists you and gets things done for you integrated deeply into our product journeys.
#ixigoNEXT #TARA #AI #TravelTech

Scaled this Account from 50k to 1 million in ~5 Months.

-Posted 40 Reels
-50M+ Accounts reached
-2 Videos 30 Million+
-Never focused on "Hashtags"
-No "SEO"
-Never "Engaged" within 1 hour of posting
-Client spent only 1 day in a month for shoot

So what did we do?

(1/n)