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Ana Sayfaya Dön

this is rare f*cking gold an internal AI engineering document leaked. it's saving solo devs $300,000 a year that number is just the three hires you never make: the one who writes the spec, the one who reviews the output, the one who runs the queue prompt-driven is out.... loop-driven is in. that shift changes everything Generate → Evaluate → Remember → Schedule → Optimize → Recurse six layers, one loop. it improves itself. no human in the middle > generation - writes its own brief, then builds against it > evaluation - a second layer grades the work and hands it back > memory - keeps what worked, so the same mistake costs you once > scheduling - picks the next job. the queue runs itself > optimization - rewrites its own instructions from what shipped > recursion - pull one layer out and the whole thing degrades that last one is the tell. six layers is the floor, not the wishlist here's the career part nobody says out loud every team already has someone typing prompts all day. nobody has the person who can build the loop that replaces that job bring this into your company and you stop being the one doing the work. you become the one who designs how the work runs that's the jump from operator to architect, and it's the promotion that's actually open right now AI stops predicting the next token. it starts running its own loop the people who wire this up over a weekend spend next year reviewing output. everyone else keeps typing promptsshow more

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26,968 görüntüleme • 22 gün önce •via X (Twitter)

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Garv Sanwariya profil fotoğrafı

Garv Sanwariya22 gün önce

the reviewer role is where people get stuck. are you running verification as an isolated sub-agent or in the same session?

かな profil fotoğrafı

かな21 gün önce

フォロー失礼します

Darshan 👨‍💻💻 profil fotoğrafı

Darshan 👨‍💻💻21 gün önce

It's good but what it's doing bad task and not monitored/reviewed ? What if we want to roll back to the point it's good like tagging

𝑨𝒇𝒓𝒊𝒏 profil fotoğrafı

𝑨𝒇𝒓𝒊𝒏21 gün önce

saving that $300k really makes sense if you cut the spec writer, reviewer and queue runner out

sophia v profil fotoğrafı

sophia v21 gün önce

Great point!

Xpress profil fotoğrafı

Xpress22 gün önce

the queue is where this gets real. one bad task sitting at the head can make every green worker look broken, so i want queue age and the oldest item on the dashboard, not just throughput.

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IF YOU ARE STILL PROMPTING BY HAND IN 2026 YOU ARE ALREADY BEHIND the guy who built Claude Code at Anthropic said he stopped writing prompts a long time ago he runs loops instead, systems that write the prompts for him and keep working while he sleeps you type one request at a time and wait for the answer he built a machine that fires hundreds of requests, checks its own output and fixes itself with no hands on the keyboard here is how you make the jump step 1 stop treating the model like a chat box and start treating it like a worker you manage step 2 write a loop that takes a goal, breaks it into tasks and sends each one to the model on its own step 3 add a second pass where the model grades its own work and retries whatever failed step 4 let it run on a timer so it keeps shipping while you are away from the screen the person still typing prompts one by one is doing the work of a intern the person running loops is doing the work of a whole team off one laptop prompting was never the skill, building the system that prompts for you is

IF YOU ARE STILL PROMPTING BY HAND IN 2026 YOU ARE ALREADY BEHIND the guy who built Claude Code at Anthropic said he stopped writing prompts a long time ago he runs loops instead, systems that write the prompts for him and keep working while he sleeps you type one request at a time and wait for the answer he built a machine that fires hundreds of requests, checks its own output and fixes itself with no hands on the keyboard here is how you make the jump step 1 stop treating the model like a chat box and start treating it like a worker you manage step 2 write a loop that takes a goal, breaks it into tasks and sends each one to the model on its own step 3 add a second pass where the model grades its own work and retries whatever failed step 4 let it run on a timer so it keeps shipping while you are away from the screen the person still typing prompts one by one is doing the work of a intern the person running loops is doing the work of a whole team off one laptop prompting was never the skill, building the system that prompts for you is

Atlas

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Boris Cherny, the engineer who built Claude Code: "I don't talk to an agent anymore. I talk to a loop" a prompt is one instruction you babysit. a loop is a goal the AI works toward on its own: > it plans > does the work > checks itself > fixes what's weak > and repeats until it's done you step out, the work keeps going that's the shift the best engineers quietly moved to. most people hear a line like that and have no idea what it means in practice this breaks it down without the hype: what a loop actually is, when it's worth building, when it's a money trap, and how to run one yourself today watch his clip, then read the article below

Boris Cherny, the engineer who built Claude Code: "I don't talk to an agent anymore. I talk to a loop" a prompt is one instruction you babysit. a loop is a goal the AI works toward on its own: > it plans > does the work > checks itself > fixes what's weak > and repeats until it's done you step out, the work keeps going that's the shift the best engineers quietly moved to. most people hear a line like that and have no idea what it means in practice this breaks it down without the hype: what a loop actually is, when it's worth building, when it's a money trap, and how to run one yourself today watch his clip, then read the article below

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PROMPTS ARE DEAD. LOOPS JUST REPLACED YOUR $200K ENGINEER. Claire Vo showed how to turn one prompt into a self-running loop. It reviews your aging pull requests every morning and hunts for new skills every week. And it spins up its own subagents to check its own work. Runs on Claude Code + Codex. One afternoon. One prompt. The numbers are insane: - Senior doing code review: $200K/year - Automation engineer: $150K/year - This setup: about $200/month - Time to build: one afternoon - Skill required: describe the job like you are onboarding a hire The opportunity is even wilder: Teams pay people to babysit pull requests and chase stale reviews. The loop does it itself at 10:15 a.m., alerts the team, and validates itself with subagents. An agency would charge thousands to wire this up. One person + Claude Code + Codex + one prompt = an engineering team that reviews code and finds new skills while you sleep. Save and watch the clip.

PROMPTS ARE DEAD. LOOPS JUST REPLACED YOUR $200K ENGINEER. Claire Vo showed how to turn one prompt into a self-running loop. It reviews your aging pull requests every morning and hunts for new skills every week. And it spins up its own subagents to check its own work. Runs on Claude Code + Codex. One afternoon. One prompt. The numbers are insane: - Senior doing code review: $200K/year - Automation engineer: $150K/year - This setup: about $200/month - Time to build: one afternoon - Skill required: describe the job like you are onboarding a hire The opportunity is even wilder: Teams pay people to babysit pull requests and chase stale reviews. The loop does it itself at 10:15 a.m., alerts the team, and validates itself with subagents. An agency would charge thousands to wire this up. One person + Claude Code + Codex + one prompt = an engineering team that reviews code and finds new skills while you sleep. Save and watch the clip.

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While AI timeline argues about loop engineering, a 20-year-old student in Shenzhen built the biggest loop anyone's aimed at money: 300 agents, one brain, $1,200 -> 395,000. Not a prompt. Not a bot. A loop that runs the whole job on its own - and never asks him a thing. No fund. No backers. Just a laptop, a dorm room, and a bet that a swarm beats a genius. His wallet: The smartest single model still works one step at a time. His loop moves in 300 directions at once - and never checks in with him. Claude Opus 4.8 runs the floor as the brain. 300 agents are the hands. One loop ties them together: > Decompose - Opus breaks the market into targets > Dispatch - 300 agents scatter across them at once > Execute - thousands of reads in a single pass, not one by one > Review - Opus grades every edge before a cent moves The hands find. The brain judges. The loop learns what failed and runs again, tighter each time. One daily loss cap, and it shuts itself down. It's not a bot you babysit. It's a loop that runs the whole desk. Everyone's just learning to run one loop. He runs 300 in one. The edge was never the genius model - it's the size of the loop, and the brain in charge of it. Save this - the full 300-agent loop is laid out above, start to finish. You'll want it when you build your own. 300 agents are looping right now, hunting the markets everyone skips. Two clicks and their trades land in your wallet too:

While AI timeline argues about loop engineering, a 20-year-old student in Shenzhen built the biggest loop anyone's aimed at money: 300 agents, one brain, $1,200 -> 395,000. Not a prompt. Not a bot. A loop that runs the whole job on its own - and never asks him a thing. No fund. No backers. Just a laptop, a dorm room, and a bet that a swarm beats a genius. His wallet: The smartest single model still works one step at a time. His loop moves in 300 directions at once - and never checks in with him. Claude Opus 4.8 runs the floor as the brain. 300 agents are the hands. One loop ties them together: > Decompose - Opus breaks the market into targets > Dispatch - 300 agents scatter across them at once > Execute - thousands of reads in a single pass, not one by one > Review - Opus grades every edge before a cent moves The hands find. The brain judges. The loop learns what failed and runs again, tighter each time. One daily loss cap, and it shuts itself down. It's not a bot you babysit. It's a loop that runs the whole desk. Everyone's just learning to run one loop. He runs 300 in one. The edge was never the genius model - it's the size of the loop, and the brain in charge of it. Save this - the full 300-agent loop is laid out above, start to finish. You'll want it when you build your own. 300 agents are looping right now, hunting the markets everyone skips. Two clicks and their trades land in your wallet too:

cvxv666

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Anthropic engineer: «You're not supposed to sit and re-prompt Claude all day. You build one loop, and it does the work while you sleep.» • 00:00 - Build your first agent that runs on its own • 05:02 - The loop that fixes its own mistakes • 16:43 - Why Claude forgets you between chats, and the fix You can learn it in one afternoon. 30 minutes here replace what most people spend a year figuring out. Watch it today, then read the guide on building loops below.

Anthropic engineer: «You're not supposed to sit and re-prompt Claude all day. You build one loop, and it does the work while you sleep.» • 00:00 - Build your first agent that runs on its own • 05:02 - The loop that fixes its own mistakes • 16:43 - Why Claude forgets you between chats, and the fix You can learn it in one afternoon. 30 minutes here replace what most people spend a year figuring out. Watch it today, then read the guide on building loops below.

Raytar

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ANTHROPIC LEAD ENGINEER MAKING $2.3M/YEAR JUST LEAKED A 12-PAGE DOCUMENT - AND GOT FIRED 15 MINUTES AFTER PUBLISHING most developers build loops - but almost every loop breaks in one of five ways, and each failure has a symptom visible from the outside without reading a single line of code > Blind loop - the agent waits for a human to hand it work every morning - automating execution but not discovery > Tangled loop - parallel agents share one directory and overwrite each other parallelism that destroys instead of multiplies > Nodding loop - the agent grades its own work and approves it every time a loop that has never said no to itself is broken > Amnesiac loop - results live only in the context window every morning the system wakes up with no memory of yesterday > Manual loop - no trigger a human presses the button to start it that is not a loop that is a script waiting for a person a real loop finds its own work - remembers what it did has something that can say no never lets two agents touch the same file and fires itself on a timer remove any one of the five - and the loop either breaks or never starts 12 pages that changed how I build agentic systems today

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Sprytix

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Claude built Claude. The current model now does most of the work of building the next one, and the next one will do more of the work on the one after that... Once that process runs on its own it hyper accelerates, because the slowest part of the loop has always been us. Emad takes it to the obvious place. How do you outcompete a company that runs entirely on agents? You dont. Cognitively the human on the team goes from the asset to the bottleneck, and thats before the models get any better, which they are, every few weeks at an ever-increasing pace. Scary if you read it as you versus the machine. But it isnt a competition... Every time tools have built tools, the people who did well werent the ones who tried to out work the machine... they were the ones who owned it. Compute, energy, the rails the agents settle on. Thats where the value pools, and for the first time in history its something anyone can own a piece of.

Claude built Claude. The current model now does most of the work of building the next one, and the next one will do more of the work on the one after that... Once that process runs on its own it hyper accelerates, because the slowest part of the loop has always been us. Emad takes it to the obvious place. How do you outcompete a company that runs entirely on agents? You dont. Cognitively the human on the team goes from the asset to the bottleneck, and thats before the models get any better, which they are, every few weeks at an ever-increasing pace. Scary if you read it as you versus the machine. But it isnt a competition... Every time tools have built tools, the people who did well werent the ones who tried to out work the machine... they were the ones who owned it. Compute, energy, the rails the agents settle on. Thats where the value pools, and for the first time in history its something anyone can own a piece of.

Raoul Pal

81,474 görüntüleme • 3 gün önce

There are two types of engineers in 2026 The first opens his laptop in the morning, writes a prompt, waits, reads the diff, fixes it, repeats The second opens his phone, checks what shipped while he was asleep Different answer to one question: who is the loop? The first engineer is the loop, he starts the agent, reviews the output, decides what's next, the moment he steps away it stops The second engineer built the system that is the loop instead of him, PR review, flaky tests, CI triage, all running without him, he just reads the report What stops most people isn't complexity It's that they never noticed they are the bottleneck Full guide to building the system that runs without you below

There are two types of engineers in 2026 The first opens his laptop in the morning, writes a prompt, waits, reads the diff, fixes it, repeats The second opens his phone, checks what shipped while he was asleep Different answer to one question: who is the loop? The first engineer is the loop, he starts the agent, reviews the output, decides what's next, the moment he steps away it stops The second engineer built the system that is the loop instead of him, PR review, flaky tests, CI triage, all running without him, he just reads the report What stops most people isn't complexity It's that they never noticed they are the bottleneck Full guide to building the system that runs without you below

plutos

14,653 görüntüleme • 3 ay önce

Automation engineer sent two AI to war. One fights to place the trade. The other fights to prove it's a mistake. Only what survives the battle gets his money - $392,000 profit of it so far. He doesn't pick the trades anymore. He built loop and stepped back. His wallet: The article below explains why that second AI, the one whose only job is to say no - is the entire game. Without a real check, you don't have a loop. You have a model agreeing with itself until the account's empty. He builds these loops for a living - agents that ship code and run themselves. One weekend he built one that trades. Here's how the war actually plays out. The maker reads the 5-minute candle and builds a case: buy Up, here's why. The checker has one purpose - break that case. Wrong regime, thin edge, bad timing. Poke one hole and the trade dies on the spot. Only the trades the checker can't kill ever reach the market. Every night the loop writes down which calls went wrong and tightens its own rules. It stops itself cold at the daily loss cap - nothing runs forever. $5,000 → $392,000. The checker vetoes far more trades than it lets through. That's the point. He didn't build a smarter bot. He built one that has to win an argument before it spends a dollar. Save this and read the breakdown below - it's the clearest explanation of loop engineering on your timeline, and it's the exact idea this whole system runs on. Or skip the build: the loop's live right now, two AI arguing over the next candle. Two clicks and its winners land in your wallet too:

Automation engineer sent two AI to war. One fights to place the trade. The other fights to prove it's a mistake. Only what survives the battle gets his money - $392,000 profit of it so far. He doesn't pick the trades anymore. He built loop and stepped back. His wallet: The article below explains why that second AI, the one whose only job is to say no - is the entire game. Without a real check, you don't have a loop. You have a model agreeing with itself until the account's empty. He builds these loops for a living - agents that ship code and run themselves. One weekend he built one that trades. Here's how the war actually plays out. The maker reads the 5-minute candle and builds a case: buy Up, here's why. The checker has one purpose - break that case. Wrong regime, thin edge, bad timing. Poke one hole and the trade dies on the spot. Only the trades the checker can't kill ever reach the market. Every night the loop writes down which calls went wrong and tightens its own rules. It stops itself cold at the daily loss cap - nothing runs forever. $5,000 → $392,000. The checker vetoes far more trades than it lets through. That's the point. He didn't build a smarter bot. He built one that has to win an argument before it spends a dollar. Save this and read the breakdown below - it's the clearest explanation of loop engineering on your timeline, and it's the exact idea this whole system runs on. Or skip the build: the loop's live right now, two AI arguing over the next candle. Two clicks and its winners land in your wallet too:

cvxv666

42,548 görüntüleme • 3 ay önce

HOW TO USE AI LOOPS TO RUN YOUR BUSINESS 24/7 A lot has been written about loop engineering for building products. Almost nothing about using loops to run the business itself. That's the bigger idea. A loop is when you give an agent a goal, a way to check its own work, and permission to keep trying until it hits that goal. Build. Verify. Repeat. Stop when the condition is met. Here's what it looks like in practice: 1/SEO loop You're position 30 for a term you want. The loop runs once a month, makes changes, checks where you rank, and keeps pushing until you're on page one. This is running in production right now on Inbox Zero. 2/Ads loop You're spending $100 a day and losing money. The loop tests creative, checks profitability, kills what fails, and keeps going until the account is in the black. 3/Eval loop Your AI feature is only 88% accurate. The loop keeps adjusting the prompt and swapping the model until it passes 90%. 4/LLM visibility loop People search in ChatGPT now, not just Google. Same loop, new scoreboard. Are we the answer or not? The whole thing hinges on one thing: a metric that comes back black and white. Where do I rank? Did it hit profitability? Did the evals pass? Give an agent that scoreboard and it runs for months. Loops used to run for 30 minutes. These run for a year. Take a step, sleep, wake up next month, take another one. You're basically hiring an agency that never sleeps, gets paid in tokens instead of invoices, and undoes its own mistakes when the number goes down. Full episode on The Startup Ideas Podcast (SIP) 🧃 watch

HOW TO USE AI LOOPS TO RUN YOUR BUSINESS 24/7 A lot has been written about loop engineering for building products. Almost nothing about using loops to run the business itself. That's the bigger idea. A loop is when you give an agent a goal, a way to check its own work, and permission to keep trying until it hits that goal. Build. Verify. Repeat. Stop when the condition is met. Here's what it looks like in practice: 1/SEO loop You're position 30 for a term you want. The loop runs once a month, makes changes, checks where you rank, and keeps pushing until you're on page one. This is running in production right now on Inbox Zero. 2/Ads loop You're spending $100 a day and losing money. The loop tests creative, checks profitability, kills what fails, and keeps going until the account is in the black. 3/Eval loop Your AI feature is only 88% accurate. The loop keeps adjusting the prompt and swapping the model until it passes 90%. 4/LLM visibility loop People search in ChatGPT now, not just Google. Same loop, new scoreboard. Are we the answer or not? The whole thing hinges on one thing: a metric that comes back black and white. Where do I rank? Did it hit profitability? Did the evals pass? Give an agent that scoreboard and it runs for months. Loops used to run for 30 minutes. These run for a year. Take a step, sleep, wake up next month, take another one. You're basically hiring an agency that never sleeps, gets paid in tokens instead of invoices, and undoes its own mistakes when the number goes down. Full episode on The Startup Ideas Podcast (SIP) 🧃 watch

GREG ISENBERG

83,349 görüntüleme • 2 ay önce

Right now, most developers are still doing the job AI should be doing. Assign a task. Wait. Review the result. Fix it. Repeat. You're not building with AI. You're babysitting it. The shift happening now is much bigger than better coding agents. It's loop engineering. Instead of managing every AI agent yourself, you build a system that manages them for you. One loop assigns the work. Another checks the output. A third retries failures. Everything keeps moving without waiting for your next prompt. Your job doesn't disappear. It changes. You stop acting like a project manager... ...and start designing the system that manages the entire team. That's exactly the transition I break down in the article below.

Right now, most developers are still doing the job AI should be doing. Assign a task. Wait. Review the result. Fix it. Repeat. You're not building with AI. You're babysitting it. The shift happening now is much bigger than better coding agents. It's loop engineering. Instead of managing every AI agent yourself, you build a system that manages them for you. One loop assigns the work. Another checks the output. A third retries failures. Everything keeps moving without waiting for your next prompt. Your job doesn't disappear. It changes. You stop acting like a project manager... ...and start designing the system that manages the entire team. That's exactly the transition I break down in the article below.

Pure

11,344 görüntüleme • 3 ay önce

ANTHROPIC LEAKED A 6-LOOP SETUP THAT REPLACES A $3,000 AGENCY AND COSTS $59 A MONTH Microsoft and Google have been running this for a while - the gap against an agency is exactly 51x. an agency charged you for waiting, not for work - the brief walked from the strategist to the copywriter to the designer for weeks. here all 6 loops read one file on the same pass - there's nobody to wait on, and the calendar is empty. 51% of the bill is production on Sonnet 5, and only 5% is strategy on Opus 5 - the priciest model runs once a week. 22% of the whole bill sits on the batch queue at half rate - where nobody is waiting for an answer right now. the journal is the only loop that writes back into the root - which angle is dead, and next week starts tighter. the 6 loops bring you 3 angles a week - the final pick stays yours, and that's the part that never automates. save this and paste it into Claude Code - the loops remove the waiting, not the judgement ↓

ANTHROPIC LEAKED A 6-LOOP SETUP THAT REPLACES A $3,000 AGENCY AND COSTS $59 A MONTH Microsoft and Google have been running this for a while - the gap against an agency is exactly 51x. an agency charged you for waiting, not for work - the brief walked from the strategist to the copywriter to the designer for weeks. here all 6 loops read one file on the same pass - there's nobody to wait on, and the calendar is empty. 51% of the bill is production on Sonnet 5, and only 5% is strategy on Opus 5 - the priciest model runs once a week. 22% of the whole bill sits on the batch queue at half rate - where nobody is waiting for an answer right now. the journal is the only loop that writes back into the root - which angle is dead, and next week starts tighter. the 6 loops bring you 3 angles a week - the final pick stays yours, and that's the part that never automates. save this and paste it into Claude Code - the loops remove the waiting, not the judgement ↓

Noisy

10,557 görüntüleme • 1 ay önce

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 görüntüleme • 1 ay önce

Someone just posted the full blueprint for an AI swarm that does the job of a 200-person quant research team. Six agents. Running 24/7. Finding brand-new alpha while you sleep. Citadel needs 100 PhDs to do this. Two Sigma needs 200. This does it with six bots and one laptop. Two ways to play this - spend a weekend building your own swarm, or copy the wallet of one that's already up $2M: Boris Cherny runs Claude Code at Anthropic. Two weeks ago he said: "I don't prompt Claude anymore. I have loops running that prompt Claude. My job is to write loops" Alpha research is just a pipeline. So instead of sitting in it, you hand each stage to its own agent: > one reads every new research paper overnight and pulls out the trade idea > one builds the features and cleans the data > one backtests it over 20 years, costs and slippage included > one runs the hard stats and kills anything overfit > one checks it still works in every market regime > one strips out plain momentum and value to see if any real edge is left Each of those six is a job a fund pays a $600,000-a-year quant to do. He runs all six for the price of an API bill. The rule that makes it work: the agent that builds a signal never gets to approve it. A separate, stronger agent tries to kill it first. Whatever survives all six by morning is real, new alpha. One trader's already running this exact swarm on Polymarket. That $2M wallet is public, every trade on-chain. The full build is in the post below - six agents, the tool that runs them, and the five mistakes that kill most people. Bookmark & read this before it's buried.

cvxv666

104,237 görüntüleme • 3 ay önce

ChatGPT can write you a thousand trading strategies from one sentence. 999 will quietly bleed your account dry. Every single one of them looks like a winner. One method pulls the real one out. Quant desks have run it for years. It's called loop engineering. It's not a smarter prompt. It's a loop: generate a strategy, test it, score why it failed, feed that back, and run it again until one survives data it has never seen. Man Group runs $150 billion. They built an AI that writes and tests hundreds of strategies a week. And second agent whose only job is to hunt the ones that secretly overfit and kill them before a cent goes live. > describe an idea -> backtest 5 years in 12 seconds > read why it died -> feed that back in > run it again until one survives data it never saw AI can write a thousand strategies. Loop engineering is the only thing that tells you which one was ever real. 89% of retail lost money in 2025. Almost none of it from bad ideas. All of it from trading the first guess and never running it through backtest loop. Horizon just put the whole thing in a chat box, free while the beta's open: You're not losing to smarter traders. You're losing to the ones who opened the tab. Anyone can generate a strategy now. Almost no one runs the loop that proves it. That gap is the whole edge. You'll mean to check it later. Later is a "waitlist closed" page.

ChatGPT can write you a thousand trading strategies from one sentence. 999 will quietly bleed your account dry. Every single one of them looks like a winner. One method pulls the real one out. Quant desks have run it for years. It's called loop engineering. It's not a smarter prompt. It's a loop: generate a strategy, test it, score why it failed, feed that back, and run it again until one survives data it has never seen. Man Group runs $150 billion. They built an AI that writes and tests hundreds of strategies a week. And second agent whose only job is to hunt the ones that secretly overfit and kill them before a cent goes live. > describe an idea -> backtest 5 years in 12 seconds > read why it died -> feed that back in > run it again until one survives data it never saw AI can write a thousand strategies. Loop engineering is the only thing that tells you which one was ever real. 89% of retail lost money in 2025. Almost none of it from bad ideas. All of it from trading the first guess and never running it through backtest loop. Horizon just put the whole thing in a chat box, free while the beta's open: You're not losing to smarter traders. You're losing to the ones who opened the tab. Anyone can generate a strategy now. Almost no one runs the loop that proves it. That gap is the whole edge. You'll mean to check it later. Later is a "waitlist closed" page.

cvxv666

174,699 görüntüleme • 3 ay önce

somebody just torched their entire career for us someone inside Anthropic wrote down exactly how they wire their AIs to work as a team instead of one at a time, every number, and let the whole thing walk out the door it's called Graph Engineering: you stop asking one AI to do the whole job and start running a crew. one plans, a few go and look, one checks the others for lies their own measurement: the crew came back with 96% of the quality at 46% of the price. same models, same question. they only changed who is allowed to talk to whom Anthropic raised $65,000,000,000 to figure this out. it costs you $0 run one tonight in a normal chat, 3 moves: 1. give it the job and make it write the plan before it touches anything 2. run each step in its own fresh chat so nothing bleeds into the next 3. in one clean chat at the end, make it check the work against sources and mark whatever it could not confirm save this, then open the piece below: how many workers a job actually needs, and where one more starts making it worse ↓

somebody just torched their entire career for us someone inside Anthropic wrote down exactly how they wire their AIs to work as a team instead of one at a time, every number, and let the whole thing walk out the door it's called Graph Engineering: you stop asking one AI to do the whole job and start running a crew. one plans, a few go and look, one checks the others for lies their own measurement: the crew came back with 96% of the quality at 46% of the price. same models, same question. they only changed who is allowed to talk to whom Anthropic raised $65,000,000,000 to figure this out. it costs you $0 run one tonight in a normal chat, 3 moves: 1. give it the job and make it write the plan before it touches anything 2. run each step in its own fresh chat so nothing bleeds into the next 3. in one clean chat at the end, make it check the work against sources and mark whatever it could not confirm save this, then open the piece below: how many workers a job actually needs, and where one more starts making it worse ↓

Argona

1,385,988 görüntüleme • 1 ay önce

Boris Cherny, Head of Claude Code, Anthropic: "you can define a stop hook that's like, if the tests don't pass, keep going. essentially it's like you can just make the model keep going until the thing is done." that one config is the post's loop #1, straight from the person who built the tool. a stop hook fires every time the turn ends, so the work can't be called done until tests and lint go green. deterministic, zero effort, the loop most people skip. cherny describes the verification loop in his own words too: for big changes his team spawns subagents to find every issue, one checking claude.md compliance, one combing git history, one hunting bugs, then five more subagents whose only job is to kill the false positives. a fresh clean-context critic catches what the builder talked itself past. and the memory loop, in his words: if you see a mistake, you just tell claude to add it to claude.md, so next time it already knows. the correction outlives the session it happened in. four loops, none exotic. each is a few lines of config or one instruction. seniors out-ship everyone else because they run all four at once, not because their model is smarter.

Boris Cherny, Head of Claude Code, Anthropic: "you can define a stop hook that's like, if the tests don't pass, keep going. essentially it's like you can just make the model keep going until the thing is done." that one config is the post's loop #1, straight from the person who built the tool. a stop hook fires every time the turn ends, so the work can't be called done until tests and lint go green. deterministic, zero effort, the loop most people skip. cherny describes the verification loop in his own words too: for big changes his team spawns subagents to find every issue, one checking claude.md compliance, one combing git history, one hunting bugs, then five more subagents whose only job is to kill the false positives. a fresh clean-context critic catches what the builder talked itself past. and the memory loop, in his words: if you see a mistake, you just tell claude to add it to claude.md, so next time it already knows. the correction outlives the session it happened in. four loops, none exotic. each is a few lines of config or one instruction. seniors out-ship everyone else because they run all four at once, not because their model is smarter.

Voltex

30,025 görüntüleme • 3 ay önce

Andrej Karpathy: "Prompting is going away. Delete everything, keep Graph." In 69 minutes he shows how to build Graphs, and why it's the only thing that will be left standing at the end Prompts → Agents → Loops → Graphs a loop keeps one agent working until the job is done a graph decides which agents exist and what each one hands to the next anyone can build an agent, almost no one builds the graph that runs them watch it today, then save the full guide on Graphs below before everyone catches up ↓

Andrej Karpathy: "Prompting is going away. Delete everything, keep Graph." In 69 minutes he shows how to build Graphs, and why it's the only thing that will be left standing at the end Prompts → Agents → Loops → Graphs a loop keeps one agent working until the job is done a graph decides which agents exist and what each one hands to the next anyone can build an agent, almost no one builds the graph that runs them watch it today, then save the full guide on Graphs below before everyone catches up ↓

Callan

499,512 görüntüleme • 13 gün önce

ANTHROPIC LEAKED A FILE THEIR LEAD ENGINEER SPENT 4 YEARS BUILDING AT A COST OF $3.2M - ONE SUPER AGENT WITH JEV HOLDS A BUSINESS DOING $2.4M A YEAR the agent costs $0, and in month one it's already pulling $100K+ read → decide → build → ship → watch → back to reading 24 cycles a day, and each one starts exactly where the last one stopped it doesn't sleep, doesn't forget and never asks what to do next in one night it runs more cycles than a team closes in a quarter JEV holds the context, the budget and the stop condition between hours - without it every cycle would start from zero it picks one change an hour, not twenty - which is exactly why nothing breaks if things get worse it rolls back on its own, no meeting and no explanation the price of the loop doesn't grow with the revenue: it's the same at $0 and at $200,000 a month $2.4M a year is 669 customers, and that's only true while all 669 keep paying every month one agent is one point of failure: the night the loop stopped, nobody noticed until morning it ships the changes, it doesn't find the customers - that part is still yours save this and paste it into Claude Code - let it build you this loop ↓

ANTHROPIC LEAKED A FILE THEIR LEAD ENGINEER SPENT 4 YEARS BUILDING AT A COST OF $3.2M - ONE SUPER AGENT WITH JEV HOLDS A BUSINESS DOING $2.4M A YEAR the agent costs $0, and in month one it's already pulling $100K+ read → decide → build → ship → watch → back to reading 24 cycles a day, and each one starts exactly where the last one stopped it doesn't sleep, doesn't forget and never asks what to do next in one night it runs more cycles than a team closes in a quarter JEV holds the context, the budget and the stop condition between hours - without it every cycle would start from zero it picks one change an hour, not twenty - which is exactly why nothing breaks if things get worse it rolls back on its own, no meeting and no explanation the price of the loop doesn't grow with the revenue: it's the same at $0 and at $200,000 a month $2.4M a year is 669 customers, and that's only true while all 669 keep paying every month one agent is one point of failure: the night the loop stopped, nobody noticed until morning it ships the changes, it doesn't find the customers - that part is still yours save this and paste it into Claude Code - let it build you this loop ↓

Sprytix

10,347 görüntüleme • 16 gün önce

Anthropic just dropped a free 1-hour AI engineering workshop On how their engineers actually build with AI in 2026: 00:26 - Why prompting is becoming the old way 16:57 - The loop that builds, tests, and fixes its own work 25:27 - How one engineer can do the work of a 5-person team 36:25 - Build your first AI loop from scratch This 1-hour watch is worth more than most paid AI engineering courses Writing code is becoming the easy part Building the loop is the new skill Bookmark and watch it today Then build your own loop with the guide below

Anthropic just dropped a free 1-hour AI engineering workshop On how their engineers actually build with AI in 2026: 00:26 - Why prompting is becoming the old way 16:57 - The loop that builds, tests, and fixes its own work 25:27 - How one engineer can do the work of a 5-person team 36:25 - Build your first AI loop from scratch This 1-hour watch is worth more than most paid AI engineering courses Writing code is becoming the easy part Building the loop is the new skill Bookmark and watch it today Then build your own loop with the guide below

Lunar

15,125 görüntüleme • 2 ay önce