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Ana Sayfaya Dön

Introducing Loopany 🔁 Stop prompting, Design the loop. A loop management space that connects to your team’s own local agents: - Scaffold loop contracts, state, and logs - Add programmable triggers - Run self-improving cycles - Start from built-in loop templates We baked in everything we’ve learned from running... show more

Jason Zhou

35,308 subscribers

32,709 görüntüleme • 2 ay önce •via X (Twitter)

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12 Yorum

Victoria profil fotoğrafı

Victoria2 ay önce

Stop prompting and design the loop instead. The shift from writing prompts to designing systems is where the real productivity gains are. Open source means anyone can fork and customize for their own workflow

Ben Freed profil fotoğrafı

Ben Freed2 ay önce

Ooohhh some really solid concepts here!!! Pointing my loop to this!

Nick Venturi profil fotoğrafı

Nick Venturi2 ay önce

prompting all day was getting tiring this is a much better way to build

Nicolas Marchildon profil fotoğrafı

Nicolas Marchildon2 ay önce

Not clear how you bring your agent.

Jason Zhou profil fotoğrafı

Jason Zhou2 ay önce

It starts a daemon on your computer so agents run on your computer with full context directly! Loopany just orchestrate

Nicolas Marchildon profil fotoğrafı

Nicolas Marchildon2 ay önce

Still not clear

Jason Zhou profil fotoğrafı

Jason Zhou2 ay önce

Just give it a try and should be clear 😅

Nicolas Marchildon profil fotoğrafı

Nicolas Marchildon2 ay önce

Are you looking for pull requests?

AI Mastery Guide profil fotoğrafı

AI Mastery Guide2 ay önce

Designing the loop instead of just prompting it is a mindset shift most people haven't made yet 🔄

Hasan Aboul Hasan profil fotoğrafı

Hasan Aboul Hasan2 ay önce

the contracts + logs part is what i care about most. self-improving cycles sound great until the agent thinks it solved the problem when it didn't. visibility is what makes it real

Dyeu.com profil fotoğrafı

Dyeu.com2 ay önce

域名出售

Quique Fdez Guerra profil fotoğrafı

Quique Fdez Guerra2 ay önce

Super nice concept! I’m working in a way to have loops and manage them in multiple VMs and soon I want to release the app to manage them too. Super cool to see some people working on different concepts

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Anushka Singh

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Today we're introducing Wave. A proactive product agent that helps teams build self-improving products. Every product team runs the same loop. Build, ship, use, learn. AI has made building and shipping extraordinarily fast. Understanding usage and learning still happen by hand. Wave runs the whole loop: - Analyzes your Amplitude data for signals across analytics, feedback, session replays, error logs, agent traces, and experiment results - Surfaces opportunities in the form of full product specs that you or your agents can approve and ship - Tracks the experiments and outcomes of what you've built so you can start the loop over again Your product learns what works and gets smarter every cycle:

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Spenser Skates

117,626 görüntüleme • 3 ay önce

Anthropic just released 5 Claude workshops on the new skill every AI builder needs: Loop Engineering: 00:00 - Stop babysitting your agents 37:07 - Build a proactive Claude Code loop 1:11:23 - Build a production-ready Managed Agent 1:38:46 - Teach agents to learn from your team 2:07:15 - Hill-climb your agent with eval loops It is a 2 hour and 25 minute blueprint for Loop Engineering: proactive workflows, managed agents, team feedback, evals, and self-improvement. Watch it today, and read the article below to improve your skills with Fable 5.

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Alex

47,626 görüntüleme • 2 ay önce

The guy who kicked off the entire "loop engineering" wave Peter Steinberger: "You shouldn't be prompting coding agents anymore. You should be designing loops that prompt your agents." One post. 6.5M views in a week. In this talk he walks the real stack: the agent loop, a verifier that fails its own work and retries, and a loop that rewrites the agent while he sleeps. Worth more than any $500 vibe-coding course. Watch it, then read the full breakdown of the 4 loops below.

The guy who kicked off the entire "loop engineering" wave Peter Steinberger: "You shouldn't be prompting coding agents anymore. You should be designing loops that prompt your agents." One post. 6.5M views in a week. In this talk he walks the real stack: the agent loop, a verifier that fails its own work and retries, and a loop that rewrites the agent while he sleeps. Worth more than any $500 vibe-coding course. Watch it, then read the full breakdown of the 4 loops below.

dunik

219,932 görüntüleme • 3 ay önce

Anthropic Research Lead: "99% of our engineers run swarms of 300+ self-improving agents" "Close the loop, give the model a way to verify its own output" In a 20-minute session, an Anthropic Team member breaks down how to build agents that improve themselves The real setup is Claude running through loops, plan mode, and dynamic workflows Better than most $300 agent courses Bookmark and watch the talk Then read the article below

Anthropic Research Lead: "99% of our engineers run swarms of 300+ self-improving agents" "Close the loop, give the model a way to verify its own output" In a 20-minute session, an Anthropic Team member breaks down how to build agents that improve themselves The real setup is Claude running through loops, plan mode, and dynamic workflows Better than most $300 agent courses Bookmark and watch the talk Then read the article below

rari

382,839 görüntüleme • 3 ay önce

Google just released free 2-hour course on full Graph & Loop engineering: 1 prompt → 100 agents → loops → graphs from 0% to 100%: 0% → 0:35 - Graph engineering from scratch 30% → 31:17 - build your first agents graph 45% → 43:40 - run hundreds agents in parallel 75% → 1:04:58 - Loop engineering: route, check, repeat 100% → 1:30:09 - self-improving graphs that work while you sleep most people keep stuffing instructions into one agent - the real upgrade is a graph that routes, checks, and rebuilds the workflow at runtime learn graph from Google, ship your first - then unlock the complete system design below ↓

Google just released free 2-hour course on full Graph & Loop engineering: 1 prompt → 100 agents → loops → graphs from 0% to 100%: 0% → 0:35 - Graph engineering from scratch 30% → 31:17 - build your first agents graph 45% → 43:40 - run hundreds agents in parallel 75% → 1:04:58 - Loop engineering: route, check, repeat 100% → 1:30:09 - self-improving graphs that work while you sleep most people keep stuffing instructions into one agent - the real upgrade is a graph that routes, checks, and rebuilds the workflow at runtime learn graph from Google, ship your first - then unlock the complete system design below ↓

codila

377,353 görüntüleme • 20 gün önce

SpaceXAI engineer (ex. Cursor): "at SpaceXAI, 95% of our code is written by AI agents. Most of engineers are running 10-20+ agents in parallel. I'm running 20+ GrokBot agents with /loop, /goal, /swarm inside pstack, which lets agents fully own, verify and ship tasks." in a 1-hour workshop, SpaceXAI engineer showed how they build self-improving coding agent team from scratch worth more than 10 paid courses on building agents watch today, then read how to build a team of self-learning GrokBot agents from scratch in article below

SpaceXAI engineer (ex. Cursor): "at SpaceXAI, 95% of our code is written by AI agents. Most of engineers are running 10-20+ agents in parallel. I'm running 20+ GrokBot agents with /loop, /goal, /swarm inside pstack, which lets agents fully own, verify and ship tasks." in a 1-hour workshop, SpaceXAI engineer showed how they build self-improving coding agent team from scratch worth more than 10 paid courses on building agents watch today, then read how to build a team of self-learning GrokBot agents from scratch in article below

Codez

25,063 görüntüleme • 1 ay önce

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

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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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

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

Anthropic just dropped 1-hour workshop on loop engineering: 1 spec → the loop → 200 features from 0% to 100%: • 10% → 5:31 - Building memory for agentic loops • 30% → 8:22 - Four files for each Loop: features.json, standards.md, progress.md, • 55% → 11:02 - The Loop: check environment → run tests → pick feature → build → test → commit • 80% → 13:06 - one feature per loop. try everything at once and context dies mid-build • 100% → 33:03 - MVP in 1 hour, every next loop under 30 minutes most people build an agent that finishes a task -Anthropic ships agentic loops that can run for days without you. watch it today - then read the full loop engineering playbook below ↓

Anthropic just dropped 1-hour workshop on loop engineering: 1 spec → the loop → 200 features from 0% to 100%: • 10% → 5:31 - Building memory for agentic loops • 30% → 8:22 - Four files for each Loop: features.json, standards.md, progress.md, • 55% → 11:02 - The Loop: check environment → run tests → pick feature → build → test → commit • 80% → 13:06 - one feature per loop. try everything at once and context dies mid-build • 100% → 33:03 - MVP in 1 hour, every next loop under 30 minutes most people build an agent that finishes a task -Anthropic ships agentic loops that can run for days without you. watch it today - then read the full loop engineering playbook below ↓

Codez

18,398 görüntüleme • 1 ay önce

Anthropic research lead: "99% of our engineers are running swarms of 300+ self-improving agents. close the agent loop. Give the model a way to verify its own output" in a 20-minute session, Anthropic team member explains how to build a model that improves itself. Claude + loops + plan mode + dynamic workflows -that’s the secret. Watch the talk, then save the playbook below.

Anthropic research lead: "99% of our engineers are running swarms of 300+ self-improving agents. close the agent loop. Give the model a way to verify its own output" in a 20-minute session, Anthropic team member explains how to build a model that improves itself. Claude + loops + plan mode + dynamic workflows -that’s the secret. Watch the talk, then save the playbook below.

Codez

668,847 görüntüleme • 3 ay önce

We tripled the fps in one day everyone!! 15 yesterday, 40 to 50 today. Day 32 of building our own community open source, open world game with a loop of AI agents. the whole day went into performance and it paid off next stop is locking 60

We tripled the fps in one day everyone!! 15 yesterday, 40 to 50 today. Day 32 of building our own community open source, open world game with a loop of AI agents. the whole day went into performance and it paid off next stop is locking 60

Ziwen

134,808 görüntüleme • 2 ay önce

Anthropic engineer: "Over 90% of Anthropic engineers use a self-improving agentic loop for coding. The key is to close the loop: give the agent a way to verify and improve its own work" In this 12-minute talk, an Anthropic engineer explains how to build an agent that continuously improves itself. Claude + routines + loops + CLAUDE.md - that's the foundation. Skip Netflix tonight. Save this post!

Anthropic engineer: "Over 90% of Anthropic engineers use a self-improving agentic loop for coding. The key is to close the loop: give the agent a way to verify and improve its own work" In this 12-minute talk, an Anthropic engineer explains how to build an agent that continuously improves itself. Claude + routines + loops + CLAUDE.md - that's the foundation. Skip Netflix tonight. Save this post!

unicode

62,153 görüntüleme • 3 ay önce

The future of vibecoding is looping. ( my recent app cnvs has done $5.7k in 5 days and was made primarily with design looping ) you can easily break free from ai slop and create designs that feel artisan and worth paying for. im begging you to bookmark this 10 min beginner guide and start setting up loops, it will change everything for you. Timestamps : 0:27 – The ultra-simple looping diagram explained 1:18 – The best loop to start with: the design loop 1:38 – Using Codex + GPT Image Gen for the mockup 3:57 – Handing the mockup to Claude Code 4:45 – Loop starts (screenshot → compare → iterate) 7:31 – Loop finished : reviewing the result

The future of vibecoding is looping. ( my recent app cnvs has done $5.7k in 5 days and was made primarily with design looping ) you can easily break free from ai slop and create designs that feel artisan and worth paying for. im begging you to bookmark this 10 min beginner guide and start setting up loops, it will change everything for you. Timestamps : 0:27 – The ultra-simple looping diagram explained 1:18 – The best loop to start with: the design loop 1:38 – Using Codex + GPT Image Gen for the mockup 3:57 – Handing the mockup to Claude Code 4:45 – Loop starts (screenshot → compare → iterate) 7:31 – Loop finished : reviewing the result

Max Blade

22,493 görüntüleme • 3 ay önce

THIS 11-PAGE CLAUDE LOOP ENGINEERING PLAYBOOK IS THE CHEAT CODE FOR SENIOR DEV PROMOTIONS typing prompts line by line won't get you hired. you need to know how to design self-prompting loops: > Discovery: agent finds its own work from logs, failing tests, and commits > Handoff: tasks execute in isolated git worktrees to prevent parallel collisions > Verification: a second reviewer agent audits the builder's code to catch blind spots > Persistence and Scheduling: code writes to disk and loops run 24/7 on a timer the shift is simple: stop prompting the agent, build the system that prompts it read the full setup blueprint 👇

THIS 11-PAGE CLAUDE LOOP ENGINEERING PLAYBOOK IS THE CHEAT CODE FOR SENIOR DEV PROMOTIONS typing prompts line by line won't get you hired. you need to know how to design self-prompting loops: > Discovery: agent finds its own work from logs, failing tests, and commits > Handoff: tasks execute in isolated git worktrees to prevent parallel collisions > Verification: a second reviewer agent audits the builder's code to catch blind spots > Persistence and Scheduling: code writes to disk and loops run 24/7 on a timer the shift is simple: stop prompting the agent, build the system that prompts it read the full setup blueprint 👇

Mr. Buzzoni

44,637 görüntüleme • 3 ay önce

Introducing watchmen. It writes the skill files your coding agents should already have from your own sessions, shared across Claude Code, Codex, and pi, so you stop paying tokens to re-explain what your agent learned last week. Local and open-source.

Introducing watchmen. It writes the skill files your coding agents should already have from your own sessions, shared across Claude Code, Codex, and pi, so you stop paying tokens to re-explain what your agent learned last week. Local and open-source.

Dria

44,130 görüntüleme • 4 ay önce

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

53,282 görüntüleme • 3 ay önce

Andrew Ng just released a free 2-hour course on complete Graph Engineering How to go from one prompt to 100 agents that loop, improve, and run without you: 09:14 - Build your first AI agent 33:11 - Run agents with loop engineering 1:02:46 - Turn agent loops into graphs 1:30:15 - Build agents that rewrite themselves 1:49:05 - Run the full graph system without you Most people are still building one agent and calling it finished Andrew Ng is already teaching everything that comes next: Prompt → Agents → Loops → Graphs → Self-Improving Systems Single agents are the old workflow Systems that improve and run without you are the next one This 2-hour course is worth more than most $500 agent engineering programs Bookmark it and watch before everyone catches up Then read how to run 1,000 agents from one prompt below ↓

Andrew Ng just released a free 2-hour course on complete Graph Engineering How to go from one prompt to 100 agents that loop, improve, and run without you: 09:14 - Build your first AI agent 33:11 - Run agents with loop engineering 1:02:46 - Turn agent loops into graphs 1:30:15 - Build agents that rewrite themselves 1:49:05 - Run the full graph system without you Most people are still building one agent and calling it finished Andrew Ng is already teaching everything that comes next: Prompt → Agents → Loops → Graphs → Self-Improving Systems Single agents are the old workflow Systems that improve and run without you are the next one This 2-hour course is worth more than most $500 agent engineering programs Bookmark it and watch before everyone catches up Then read how to run 1,000 agents from one prompt below ↓

reira

14,729 görüntüleme • 29 gün önce

Amazon AI engineer just explained how to build agentic loops from scratch in under 10-minutes. this is one of the clearest explanations of AI agentic loops you’ll find anywhere. Loop + model + agent + hooks + MCP = an autonomous, self-improving system. People are paying $500 for courses that teach less than this. Watch it, then read the step-by-step guide below on building loops for your own agents.

Amazon AI engineer just explained how to build agentic loops from scratch in under 10-minutes. this is one of the clearest explanations of AI agentic loops you’ll find anywhere. Loop + model + agent + hooks + MCP = an autonomous, self-improving system. People are paying $500 for courses that teach less than this. Watch it, then read the step-by-step guide below on building loops for your own agents.

Codez

27,810 görüntüleme • 3 ay önce