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someone just open-sourced the entire "loop engineering" playbook. for free. 8.6k stars on github for loop engineering not prompts. loops. everything you need to build autonomous AI systems: → scheduling → memory & state → planning → sub-agents → verification → worktrees → MCP → stop conditions → safety...

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Rahul

149,662 subscribers

65,842 次观看 • 3 个月前 •via X (Twitter)

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THE LOOP ENGINEERING SETUP THAT LETS CLAUDE RUN YOUR WORK FOR HOURS WITHOUT YOU you sit there babysitting it prompt by prompt other people set the loop up once and let Claude plan, act, verify and fix its own work with nobody at the keyboard that gap is the whole skill of loop engineering the 3 resources that actually teach it, in the order i'd read them: > Claude's "Getting started with loops" - the cleanest entry point, straight from the Claude team ↳ > Claude loop engineering: how to build an agent that works while you sleep - the full roadmap from a single prompt to a loop that runs overnight ↳ > the Loop Engineering orange book - the deep conceptual breakdown, for when you want the whole mental model ↳ entry point, then practice, then the concept. that order saves you a week learn this and the work that eats your whole day starts running without you
0:12

THE LOOP ENGINEERING SETUP THAT LETS CLAUDE RUN YOUR WORK FOR HOURS WITHOUT YOU you sit there babysitting it prompt by prompt other people set the loop up once and let Claude plan, act, verify and fix its own work with nobody at the keyboard that gap is the whole skill of loop engineering the 3 resources that actually teach it, in the order i'd read them: > Claude's "Getting started with loops" - the cleanest entry point, straight from the Claude team ↳ > Claude loop engineering: how to build an agent that works while you sleep - the full roadmap from a single prompt to a loop that runs overnight ↳ > the Loop Engineering orange book - the deep conceptual breakdown, for when you want the whole mental model ↳ entry point, then practice, then the concept. that order saves you a week learn this and the work that eats your whole day starts running without you

Mr. Buzzoni

18,365 次观看 • 2 个月前

Speaking of Loop Engineering... Did you know Claude Code already has /loop built in?
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Speaking of Loop Engineering... Did you know Claude Code already has /loop built in?

Dan McAteer

104,490 次观看 • 5 个月前

Anthropic CEO after realizing a Chinese dev explained loop vs graph engineering better than anyone at the company
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Anthropic CEO after realizing a Chinese dev explained loop vs graph engineering better than anyone at the company

Kirill

1,428,058 次观看 • 2 个月前

A TEAM JUST DEPLOYED 15 AUTONOMOUS LOOP AGENTS FROM A SINGLE PROMPT USING APPLIED GRAPH ENGINEERING Most developers still manually hardcode multi agent systems, writing separate logic for every individual task. Graph engineering changes this by using a central topological map to spin up all 15 nodes simultaneously. A single 200 word input generates the architecture, routing 120 unique pathways between agents instantly. Instead of failing under conflicting instructions, these loop agents self correct via continuous state sharing. Managing a 15 node mesh requires high token throughput, making this dependent on strict low-] latency API tiers. See exactly how this automated multi agent graph architecture actually operates in real time ↓
0:15

A TEAM JUST DEPLOYED 15 AUTONOMOUS LOOP AGENTS FROM A SINGLE PROMPT USING APPLIED GRAPH ENGINEERING Most developers still manually hardcode multi agent systems, writing separate logic for every individual task. Graph engineering changes this by using a central topological map to spin up all 15 nodes simultaneously. A single 200 word input generates the architecture, routing 120 unique pathways between agents instantly. Instead of failing under conflicting instructions, these loop agents self correct via continuous state sharing. Managing a 15 node mesh requires high token throughput, making this dependent on strict low-] latency API tiers. See exactly how this automated multi agent graph architecture actually operates in real time ↓

slash1s

302,933 次观看 • 3 个月前

You’ve heard of German engineering, this is Italian engineering
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You’ve heard of German engineering, this is Italian engineering

𝖓𝖎𝖓𝖊 🕯

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⛏️ The Tunnel of Eupalinos: A 2,500-Year-Old Engineering Marvel Hidden beneath the island of Samos, Greece, the Tunnel of Eupalinos is one of the most remarkable engineering feats of the ancient world.
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⛏️ The Tunnel of Eupalinos: A 2,500-Year-Old Engineering Marvel Hidden beneath the island of Samos, Greece, the Tunnel of Eupalinos is one of the most remarkable engineering feats of the ancient world.

Unearthed 🏺

25,341 次观看 • 3 个月前

⛏️ The Tunnel of Eupalinos: A 2,500-Year-Old Engineering Marvel Hidden beneath the island of Samos, Greece, the Tunnel of Eupalinos is one of the most remarkable engineering feats of the ancient world.
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⛏️ The Tunnel of Eupalinos: A 2,500-Year-Old Engineering Marvel Hidden beneath the island of Samos, Greece, the Tunnel of Eupalinos is one of the most remarkable engineering feats of the ancient world.

Unearthed 🏺

11,840 次观看 • 16 天前

Starship is one of the hardest engineering challenges that exist…
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Starship is one of the hardest engineering challenges that exist…

ElonVision🚀

11,254 次观看 • 3 个月前

There are over 1,000 engineering blogs. Here are my top 9 favorites: - Netflix TechBlog - Uber Blog - Cloudflare Blog - Engineering at Meta - LinkedIn Engineering - Discord Blog - AWS Architecture - Slack Engineering - Stripe Blog Over to you - What are some of your favorite engineering blogs? – Subscribe to our weekly newsletter to get a Free System Design PDF (158 pages):
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There are over 1,000 engineering blogs. Here are my top 9 favorites: - Netflix TechBlog - Uber Blog - Cloudflare Blog - Engineering at Meta - LinkedIn Engineering - Discord Blog - AWS Architecture - Slack Engineering - Stripe Blog Over to you - What are some of your favorite engineering blogs? – Subscribe to our weekly newsletter to get a Free System Design PDF (158 pages):

Alex Xu

69,276 次观看 • 2 年前

Fable 5 dropping again is the biggest AI moment of the year. It’s also a usage limit trap if you don’t know what you’re doing. I just mapped out the full system to run it at 10x lower cost: - 10-80-10 framework - Model routing table - Loop engineering - Codex setup - Context memory - And every mistake that burns your limit in the first hour Don’t open Fable again until you read this.
0:13

Fable 5 dropping again is the biggest AI moment of the year. It’s also a usage limit trap if you don’t know what you’re doing. I just mapped out the full system to run it at 10x lower cost: - 10-80-10 framework - Model routing table - Loop engineering - Codex setup - Context memory - And every mistake that burns your limit in the first hour Don’t open Fable again until you read this.

CyrilXBT

33,834 次观看 • 4 个月前

holy f*ck, someone just dropped an entire reverse engineering degree on GitHub for free. Now you can build agents that can reverse engineer almost anything: 1. Ghidra How to read any binary. The NSA’s reverse engineering framework. Where almost everyone starts. 2. radare2 The same skill, but in the terminal. UNIX-style reverse engineering framework and command-line toolset. 3. LLM4Decompile An LLM that decompiles. Turns binary code into readable C. The 9B v2 model hits 64.9% re-executability on its own benchmark. 4. r2ai An LLM inside radare2. LLM-powered reversing for radare2. This is where AI starts reading the binary with you. 5. ida-pro-mcp Let the agent drive the tool. Bridges IDA Pro to language models through MCP. 6. reverse-engineering-assistant The same thing for Ghidra. An MCP server for reverse engineering tasks inside Ghidra. 7. REA Agents that reverse engineer anything. 35 target types: native binaries, APKs, firmware, websites, Electron apps, and more. Every finding is backed by evidence. Read the full REA guide below ↓
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holy f*ck, someone just dropped an entire reverse engineering degree on GitHub for free. Now you can build agents that can reverse engineer almost anything: 1. Ghidra How to read any binary. The NSA’s reverse engineering framework. Where almost everyone starts. 2. radare2 The same skill, but in the terminal. UNIX-style reverse engineering framework and command-line toolset. 3. LLM4Decompile An LLM that decompiles. Turns binary code into readable C. The 9B v2 model hits 64.9% re-executability on its own benchmark. 4. r2ai An LLM inside radare2. LLM-powered reversing for radare2. This is where AI starts reading the binary with you. 5. ida-pro-mcp Let the agent drive the tool. Bridges IDA Pro to language models through MCP. 6. reverse-engineering-assistant The same thing for Ghidra. An MCP server for reverse engineering tasks inside Ghidra. 7. REA Agents that reverse engineer anything. 35 target types: native binaries, APKs, firmware, websites, Electron apps, and more. Every finding is backed by evidence. Read the full REA guide below ↓

cabbit

20,375 次观看 • 7 天前

loop engineering worked for 6 months. then one pipeline forced a graph a loop is one agent on discover → plan → execute → verify, until a stop condition hits enough for most agent work: failing tests, draft + self-review, inbox triage, one research writeup the break is nameable: if the thing that produced the output also grades it, you don't have quality control, you have a rubber stamp his numbers before the split: 40 drafts 31 passed self-review 18 actually publish-ready on manual read gap = 13 drafts with a passing grade from a biased judge he split one loop into 3 nodes - researcher · sources + notes only - writer · notes + task only · never grades itself - reviewer · separate model call · check the bar · write nothing same 40-draft workload. manual approval 18/40 → 33/40. reviewer rejected 14 with quotable reasons. 2 escalated to human instead of burning tokens forever approval 45% → 82.5%. inference cost +60% worth it when a bad draft costs more than three model calls. not worth it for "fix the failing test" playbook: - 1 law · producer never grades - 1 router · ship / retry / escalate - 1 state object · one owner per field · guarded writes - split the verifier first · cheapest highest-leverage move loop engineering → graph engineering. not five nodes for vibes, one split verifier when the loop starts grading its own homework full contracts, router, and decision function in the article
0:15

loop engineering worked for 6 months. then one pipeline forced a graph a loop is one agent on discover → plan → execute → verify, until a stop condition hits enough for most agent work: failing tests, draft + self-review, inbox triage, one research writeup the break is nameable: if the thing that produced the output also grades it, you don't have quality control, you have a rubber stamp his numbers before the split: 40 drafts 31 passed self-review 18 actually publish-ready on manual read gap = 13 drafts with a passing grade from a biased judge he split one loop into 3 nodes - researcher · sources + notes only - writer · notes + task only · never grades itself - reviewer · separate model call · check the bar · write nothing same 40-draft workload. manual approval 18/40 → 33/40. reviewer rejected 14 with quotable reasons. 2 escalated to human instead of burning tokens forever approval 45% → 82.5%. inference cost +60% worth it when a bad draft costs more than three model calls. not worth it for "fix the failing test" playbook: - 1 law · producer never grades - 1 router · ship / retry / escalate - 1 state object · one owner per field · guarded writes - split the verifier first · cheapest highest-leverage move loop engineering → graph engineering. not five nodes for vibes, one split verifier when the loop starts grading its own homework full contracts, router, and decision function in the article

seeco

14,534 次观看 • 3 个月前

This is (part of the reason) RF engineering is scary
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This is (part of the reason) RF engineering is scary

Daniel Bogdanoff

28,223 次观看 • 8 个月前

I use Flot AI because I’m tired of thinking about prompts. Not because I don’t know how — but because I don’t want to stop my work just to phrase things perfectly. Most AI tools still expect you to: pause, think, rewrite the question, tweak the prompt. Flot AI doesn’t. It already has strong built-in prompts for everyday work: rewriting, polishing, translating, summarizing. I just select what I’m working on and ask — no prompt engineering, no overthinking. The best part is that it works in place. Emails, docs, articles — I stay where I am, get the result, keep going. When AI stops demanding “better prompts,” it finally becomes what it should be:a quiet assistant, not another task.
0:17

I use Flot AI because I’m tired of thinking about prompts. Not because I don’t know how — but because I don’t want to stop my work just to phrase things perfectly. Most AI tools still expect you to: pause, think, rewrite the question, tweak the prompt. Flot AI doesn’t. It already has strong built-in prompts for everyday work: rewriting, polishing, translating, summarizing. I just select what I’m working on and ask — no prompt engineering, no overthinking. The best part is that it works in place. Emails, docs, articles — I stay where I am, get the result, keep going. When AI stops demanding “better prompts,” it finally becomes what it should be:a quiet assistant, not another task.

Pushpendra Tripathi

88,794 次观看 • 10 个月前

Engineering is about innovation, but it’s also about safety.
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Engineering is about innovation, but it’s also about safety.

Chandana 🌻✨

5,477,626 次观看 • 4 个月前

Using Groq Inc to instantly refactor and document code. The implications for software engineering are wild. Gone are the days of waiting on an LLM for suggestions or code changes. Now, it's an instant feedback loop. Demo link in the comments:
0:16

Using Groq Inc to instantly refactor and document code. The implications for software engineering are wild. Gone are the days of waiting on an LLM for suggestions or code changes. Now, it's an instant feedback loop. Demo link in the comments:

Matt Shumer

571,484 次观看 • 2 年前

Weather Manipulation Is Already Being Used, You’re Being Lied To This is known as a scalar square. It is created by scalar low frequency emission into the stratosphere that manipulates the movement of water vapor systems. Yes… Weather engineering by is taking place and has been for a very long time. Geo Engineering, Climate Engineering, Weather Modification has been admitted to being practiced by the CIA, what else are they doing?
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Weather Manipulation Is Already Being Used, You’re Being Lied To This is known as a scalar square. It is created by scalar low frequency emission into the stratosphere that manipulates the movement of water vapor systems. Yes… Weather engineering by is taking place and has been for a very long time. Geo Engineering, Climate Engineering, Weather Modification has been admitted to being practiced by the CIA, what else are they doing?

Wall Street Apes

547,133 次观看 • 3 年前

The next-generation Tesla Roadster is a masterpiece work of engineering.
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The next-generation Tesla Roadster is a masterpiece work of engineering.

TESLA CARS ONLY⚡️

15,054 次观看 • 1 年前