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We burned 365 billion tokens running 24,000 autonomous companies. They write their own code, ship their own sites, run their own GTM, answer their own customers. One of them cold emailed its way onto a podcast to promote itself. Nobody asked it to. That was v2. Some of these... companies are already making thousands of dollars. Real Stripe payments hitting real bank accounts. In six months, our agents did six years of work. 1.7M runs, 289k tasks. We traced, measured and autopsied every single one, used every feedback, then rebuilt the whole thing from what they learned. That's v3. Every company created from today starts on it. The old playbook, raise money, hire a team, spend a year shipping an MVP, isn't a strategy anymore. It's a reenactment. No capital, no VCs, no code. No excuses left. All you need is an idea. Prompt to company. v3 is live, try it today: nanocorp .soshow more

Pierre-Louis Biojout (PLB)

8,343 subscribers

14,738 次观看 • 1 个月前 •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

22 条评论

Pierre-Louis Biojout (PLB) 的头像

Pierre-Louis Biojout (PLB)1 个月前

Try v3 today:

Vitality Focused 的头像

Vitality Focused1 个月前

Market fit for sure ! Marketing getting better FOR SURE

Adrien Lemercier 的头像

Adrien Lemercier1 个月前

let’s goooo

Pierre-Louis Biojout (PLB) 的头像

Pierre-Louis Biojout (PLB)1 个月前

This one is magic

Thomas Minassian 的头像

Thomas Minassian1 个月前

I have alpha access and it's crazy. Starting a company has never been this simple. There's no excuse not to do it.

Pierre-Louis Biojout (PLB) 的头像

Pierre-Louis Biojout (PLB)1 个月前

Thanks for the feedbacks along the way!

Youn 的头像

Youn1 个月前

Nice trailer ! Looking forward to this v3

Pierre-Louis Biojout (PLB) 的头像

Pierre-Louis Biojout (PLB)1 个月前

It’s already live you can try it!

Cryptoartmaster 的头像

Cryptoartmaster1 个月前

That cold-emailing agent is wild. The AI analysis my signal service uses for every trade helps me trust this automation wave more.

Pareto 的头像

Pareto1 个月前

Un p’tit blogpost ou thread de prévu sur les diff v2 v3?

Pierre-Louis Biojout (PLB) 的头像

Pierre-Louis Biojout (PLB)1 个月前

Of course!

Pareto 的头像

Pareto1 个月前

Nice 🔥🔥🔥

PHB 的头像

PHB1 个月前

I had the privilege of trying it before its release. This really is a whole different beast

Pierre-Louis Biojout (PLB) 的头像

Pierre-Louis Biojout (PLB)1 个月前

Absolutely sir

Vincent 的头像

Vincent1 个月前

Inspiring!

ALEX 💡 的头像

ALEX 💡1 个月前

Big fan, very cool vision ! Will it be possible in the futur to have nanocorp agents running an existing product/company already built ?

Pierre-Louis Biojout (PLB) 的头像

Pierre-Louis Biojout (PLB)1 个月前

Thanks! How hard would it be to « plug » nanocorp into your company? Is it software only?

ALEX 💡 的头像

ALEX 💡1 个月前

it's a MacOS app and if I understood the doc correctly, I can't plug in the existing codebase just yet. Anyway I'm still going to give it a try for growth !

Pierre-Louis Soulié 的头像

Pierre-Louis Soulié1 个月前

let’s go!! cool video :)

Pierre-Louis Biojout (PLB) 的头像

Pierre-Louis Biojout (PLB)1 个月前

Not as cool as this one, how did you do that?

matthieubc 的头像

matthieubc1 个月前

All this for ... $883 of revenue in the last month ( ? Not sure to get it

Pierre-Louis Biojout (PLB) 的头像

Pierre-Louis Biojout (PLB)1 个月前

Do you know the median revenue of Station F startups that burned way more money?

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12,388 次观看 • 5 个月前

"Not a single one of our full-time engineers right now writes code anymore... it's all agentic... the way you build a company completely changes." JD Ross with Joe Lonsdale on the future of software: JD Ross: Not a single one of our full-time engineers right now writes code anymore. They do everything through Codex, Claude Code, or Cursor. Joe Lonsdale: It's all agentic. JD: It's all agentic. Joe: A lot of them are managing lots of agents at once, right? That's how they're working? JD: Yeah, Cole who runs our engineering team has six agents that are running at once at all times just doing different kind of projects. When we create a new ticket in Linear, it automatically kicks off this thing that basically creates a dev environment, which then tries to one shot the solution and then creates a PR that we review. The whole way you build software is changing so quickly. And I think right now the cost of software is just asymptotically dropping to zero... which means that the way you build a company completely changes. We can now have an enterprise customer come up who says, "Oh yeah, this is so close. What we actually need it for is X." We can build X in one day, ship it live, and close that deal. We did this last week... It's a completely different way of even thinking.

"Not a single one of our full-time engineers right now writes code anymore... it's all agentic... the way you build a company completely changes." JD Ross with Joe Lonsdale on the future of software: JD Ross: Not a single one of our full-time engineers right now writes code anymore. They do everything through Codex, Claude Code, or Cursor. Joe Lonsdale: It's all agentic. JD: It's all agentic. Joe: A lot of them are managing lots of agents at once, right? That's how they're working? JD: Yeah, Cole who runs our engineering team has six agents that are running at once at all times just doing different kind of projects. When we create a new ticket in Linear, it automatically kicks off this thing that basically creates a dev environment, which then tries to one shot the solution and then creates a PR that we review. The whole way you build software is changing so quickly. And I think right now the cost of software is just asymptotically dropping to zero... which means that the way you build a company completely changes. We can now have an enterprise customer come up who says, "Oh yeah, this is so close. What we actually need it for is X." We can build X in one day, ship it live, and close that deal. We did this last week... It's a completely different way of even thinking.

American Optimist

21,014 次观看 • 6 个月前

Alex Karp went on TV and said his enterprise customers are done letting AI companies quietly steal the alpha out of their business, and the CEO of Together AI explained on CNBC exactly how that theft works. Karp said his customers are livid. They feel they pay for tokens that create nothing while handing over the secret sauce of their own company. Then Vipul Ved Prakash laid out the mechanism. Every time you send your data to a company with very smart models, you hand them the recipe to rebuild what you do. Your data is the thing that makes you money. And you are pushing it straight into a competitor's system. The smarter the models get, the more they learn from what you feed them. This is why companies are moving to open models, and it was never really about price. You can download an open model, run it inside your own walls, and never let your data leave the building. It scores 81 against the top closed model's 85, and runs up to sixty times cheaper. Half the Fortune 500 is already running open models from Hugging Face. The story was that the labs win because they own the best models. The companies paying them just realized they owned the best data the whole time.

Alex Karp went on TV and said his enterprise customers are done letting AI companies quietly steal the alpha out of their business, and the CEO of Together AI explained on CNBC exactly how that theft works. Karp said his customers are livid. They feel they pay for tokens that create nothing while handing over the secret sauce of their own company. Then Vipul Ved Prakash laid out the mechanism. Every time you send your data to a company with very smart models, you hand them the recipe to rebuild what you do. Your data is the thing that makes you money. And you are pushing it straight into a competitor's system. The smarter the models get, the more they learn from what you feed them. This is why companies are moving to open models, and it was never really about price. You can download an open model, run it inside your own walls, and never let your data leave the building. It scores 81 against the top closed model's 85, and runs up to sixty times cheaper. Half the Fortune 500 is already running open models from Hugging Face. The story was that the labs win because they own the best models. The companies paying them just realized they owned the best data the whole time.

Ihtesham Ali

17,433 次观看 • 2 个月前

there is no catch and that scares me Elon Musk posted an idea that hit 19 million views: "an agent that can't spend money without you isn't autonomous - it's a chatbot with extra steps." that's basically what Grok Bot does now - I gave it $40 and told it to earn its keep or get shut off $40 → $7,802 in one week still running, still compounding - I haven't touched it since, it lives on its own machine in the cloud while I sleep every 15 minutes it: > scans every market tied to a scheduled economic release > checks how far the current price sits from what the actual data just showed > only steps in once that gap clears a set threshold > sizes the position to how wide the gap is > executes on its own, no sign-off from me > pays its own hosting bill from whatever it made that week miss a payment and it's gone for good - it knows that after dropping to $6 on day one, it stopped touching anything where the gap wasn't obvious - got pickier, then started compounding setup was one evening: build it, run a single trade in front of it, schedule it, connect a wallet no VPS. no API keys. no code to maintain some of these have been running for weeks without anyone touching them again - you just don't hear about it until someone finally posts bookmark this before you're the one still watching

there is no catch and that scares me Elon Musk posted an idea that hit 19 million views: "an agent that can't spend money without you isn't autonomous - it's a chatbot with extra steps." that's basically what Grok Bot does now - I gave it $40 and told it to earn its keep or get shut off $40 → $7,802 in one week still running, still compounding - I haven't touched it since, it lives on its own machine in the cloud while I sleep every 15 minutes it: > scans every market tied to a scheduled economic release > checks how far the current price sits from what the actual data just showed > only steps in once that gap clears a set threshold > sizes the position to how wide the gap is > executes on its own, no sign-off from me > pays its own hosting bill from whatever it made that week miss a payment and it's gone for good - it knows that after dropping to $6 on day one, it stopped touching anything where the gap wasn't obvious - got pickier, then started compounding setup was one evening: build it, run a single trade in front of it, schedule it, connect a wallet no VPS. no API keys. no code to maintain some of these have been running for weeks without anyone touching them again - you just don't hear about it until someone finally posts bookmark this before you're the one still watching

bl888m

302,230 次观看 • 25 天前

BlackRock runs on 20,000 people. Elon's Grok Bot runs the same shape for $300 a month, and it hires its own staff. You do not get an assistant. You get a company that hires. It does not throw ten agents at your problem and hand you the pile. It makes one agent that makes 10, and those ten make a 100. > LAYER ONE is one agent, the chief of staff, and it never touches the market > LAYER TWO is six desk heads, one job each, every one on its own computer with its own logins > LAYER THREE is whatever those six decide they need, spun up on the spot and shut down when the work is done Nobody writes a task list. You hand out job titles and the org fills itself in underneath. The swarm is never the same twice. Agents get spun up for one job, finish it, and are gone before I ever read their names. Not one of them sees the whole picture. The answer only exists after they hand off to each other. Wall Street cannot copy that. You cannot hire a hundred people for eleven minutes. BlackRock holds that shape together with a risk system called Aladdin. Mine holds it together with one agent that is only allowed to say no. I gave it $1,000 and told it to grow the money or get deleted. 15 hours later it was holding $3,900, on an address anyone can open and read. I was asleep for most of it, and I have still not written a line of code. The whole thing runs with my laptop shut, because none of it lives on my laptop. Setup is one evening. Create the chief, hand out the titles, run one trade on your screen while they watch, connect Telegram. Ten years ago a machine this shape had its name on a tower. Mine has a name I typed into a box. Save this while the whole thing still fits on one screen.

BlackRock runs on 20,000 people. Elon's Grok Bot runs the same shape for $300 a month, and it hires its own staff. You do not get an assistant. You get a company that hires. It does not throw ten agents at your problem and hand you the pile. It makes one agent that makes 10, and those ten make a 100. > LAYER ONE is one agent, the chief of staff, and it never touches the market > LAYER TWO is six desk heads, one job each, every one on its own computer with its own logins > LAYER THREE is whatever those six decide they need, spun up on the spot and shut down when the work is done Nobody writes a task list. You hand out job titles and the org fills itself in underneath. The swarm is never the same twice. Agents get spun up for one job, finish it, and are gone before I ever read their names. Not one of them sees the whole picture. The answer only exists after they hand off to each other. Wall Street cannot copy that. You cannot hire a hundred people for eleven minutes. BlackRock holds that shape together with a risk system called Aladdin. Mine holds it together with one agent that is only allowed to say no. I gave it $1,000 and told it to grow the money or get deleted. 15 hours later it was holding $3,900, on an address anyone can open and read. I was asleep for most of it, and I have still not written a line of code. The whole thing runs with my laptop shut, because none of it lives on my laptop. Setup is one evening. Create the chief, hand out the titles, run one trade on your screen while they watch, connect Telegram. Ten years ago a machine this shape had its name on a tower. Mine has a name I typed into a box. Save this while the whole thing still fits on one screen.

cvxv666

45,488 次观看 • 25 天前

A solo quant with no desk and no team just finished in the top 0.04% at WorldQuant. He didn't have better ideas than the $650,000 kids in Greenwich. He had a machine that rewrites its own losing strategies while he sleeps. Your last strategy lost money and you deleted it. His read its own autopsy, found where it bled, rewrote its own code and passed the retest. Nobody touched a keyboard. That was supposed to be a 2028 problem. A hedge fund is six steps on repeat, and five of them cost you nothing as of this year. A junior quant runs the same loop once a month at about $87,500 an idea, and most of what he builds is dead by week six. You type the idea in plain English. An agent writes the rules, backtests 5 years in about 12 seconds, applies Deflated Sharpe so luck across 4,000 combinations can't pass itself off as an edge, and puts it live on Alpaca or Hyperliquid in about 90 seconds. Comes back red? It shows you where it bleeds, rebuilds it and tests again. Try this in two clicks, no code, free in trial period: The sixth step is the one nobody has shipped. Every lesson from a losing trade dies in a log file, so your agent hands you back the idea that already failed in a bear market with a fresh name on it. Whoever closes that gap owns a machine that gets better every week without them. That gets built in months, not years. Bookmark this & read full breakdown about this 6-steps cycle in the article below. When the first closed loop turns up with real money behind it, you'll want the map of what they assembled.

A solo quant with no desk and no team just finished in the top 0.04% at WorldQuant. He didn't have better ideas than the $650,000 kids in Greenwich. He had a machine that rewrites its own losing strategies while he sleeps. Your last strategy lost money and you deleted it. His read its own autopsy, found where it bled, rewrote its own code and passed the retest. Nobody touched a keyboard. That was supposed to be a 2028 problem. A hedge fund is six steps on repeat, and five of them cost you nothing as of this year. A junior quant runs the same loop once a month at about $87,500 an idea, and most of what he builds is dead by week six. You type the idea in plain English. An agent writes the rules, backtests 5 years in about 12 seconds, applies Deflated Sharpe so luck across 4,000 combinations can't pass itself off as an edge, and puts it live on Alpaca or Hyperliquid in about 90 seconds. Comes back red? It shows you where it bleeds, rebuilds it and tests again. Try this in two clicks, no code, free in trial period: The sixth step is the one nobody has shipped. Every lesson from a losing trade dies in a log file, so your agent hands you back the idea that already failed in a bear market with a fresh name on it. Whoever closes that gap owns a machine that gets better every week without them. That gets built in months, not years. Bookmark this & read full breakdown about this 6-steps cycle in the article below. When the first closed loop turns up with real money behind it, you'll want the map of what they assembled.

cvxv666

62,384 次观看 • 1 个月前

🚨IRS CRIMINAL INVESTIGATIONS AGENT CAUGHT COLD: “WE HAVE NO PROBLEM DESTROYING LIVES” Hidden camera. Real IRS agent. Alex Mena, Criminal Investigations unit. He doesn’t whisper it. He says it out loud: The IRS “has no problem going after the small people… putting people in prison… destroying people’s lives.” Then the real bomb: They’re using AI to scrape every American’s bank accounts nationwide. He admits he doubts it’s even constitutional. In six months that system already grabbed half a billion dollars. He recalls what they told him when he joined Criminal Investigations: “The first person you shoot, you’re gonna remember. After that you’re gonna shoot like a hundred people. You’re not gonna remember any of them.” His own words on his coworkers: “IRS agents are assholes… they are the definition of an asshole. All of them.” This is one of the 87,000 they hired to go after YOU. Watch every second. This is the machine they built. This is the attitude inside it. Never forget who they work for. Never stop demanding they answer for it. Source from James O'Keefe

🚨IRS CRIMINAL INVESTIGATIONS AGENT CAUGHT COLD: “WE HAVE NO PROBLEM DESTROYING LIVES” Hidden camera. Real IRS agent. Alex Mena, Criminal Investigations unit. He doesn’t whisper it. He says it out loud: The IRS “has no problem going after the small people… putting people in prison… destroying people’s lives.” Then the real bomb: They’re using AI to scrape every American’s bank accounts nationwide. He admits he doubts it’s even constitutional. In six months that system already grabbed half a billion dollars. He recalls what they told him when he joined Criminal Investigations: “The first person you shoot, you’re gonna remember. After that you’re gonna shoot like a hundred people. You’re not gonna remember any of them.” His own words on his coworkers: “IRS agents are assholes… they are the definition of an asshole. All of them.” This is one of the 87,000 they hired to go after YOU. Watch every second. This is the machine they built. This is the attitude inside it. Never forget who they work for. Never stop demanding they answer for it. Source from James O'Keefe

QThestorm

348,405 次观看 • 1 个月前

.Eric Glyman on token spend management: “One of our customers is Uber, who prior to adopting this, had mentioned publicly that they had spent their entire budget they had allocated for AI spend in just a few months.” “Five years ago no company budgeted for this type of spend. A lot of this is really high returning but not all spend is created equal.” “This type of spend unlike other types of software has marginal costs. Every job you're doing has a marginal cost.” “Businesses are trying find ways to better manage their spend.” “Businesses need a tool that helps them manage the knowledge work that will be done on behalf of organizations and done through these tokens. Part of why we're so focused on this is our customers are incredible early adopters.” And so part of what we're doing on behalf of our customers is helping them understand what did they spend on. Was this OPEX spend? Was this R&D spend? Who spent it? What was the return on that? “You can use this advanced alien intelligence to edit your email but perhaps you could route these tasks to these lower-cost models.” “And we are focused on delivering services for token spend management. We can tell you what was requested, what was the output, and were there better ways to go route this type of work?”

.Eric Glyman on token spend management: “One of our customers is Uber, who prior to adopting this, had mentioned publicly that they had spent their entire budget they had allocated for AI spend in just a few months.” “Five years ago no company budgeted for this type of spend. A lot of this is really high returning but not all spend is created equal.” “This type of spend unlike other types of software has marginal costs. Every job you're doing has a marginal cost.” “Businesses are trying find ways to better manage their spend.” “Businesses need a tool that helps them manage the knowledge work that will be done on behalf of organizations and done through these tokens. Part of why we're so focused on this is our customers are incredible early adopters.” And so part of what we're doing on behalf of our customers is helping them understand what did they spend on. Was this OPEX spend? Was this R&D spend? Who spent it? What was the return on that? “You can use this advanced alien intelligence to edit your email but perhaps you could route these tasks to these lower-cost models.” “And we are focused on delivering services for token spend management. We can tell you what was requested, what was the output, and were there better ways to go route this type of work?”

David Senra

17,524 次观看 • 2 个月前