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Built a Self Executing Agent Loop that can run 300 agents through 4,000 steps without needing a human to restart the process. - 300 agents. - 4,000 steps per run. - 5 live data feeds. - 3 verification passes. The important part isn't the agent count. It's that the... show more

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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

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we built autonomous AI agents that hunt illegal online gambling networks in Indonesia. the agent discovers sites on its own, actually registers (!!), and extracts the financial accounts behind the operations. take a look at our codex-powered agent navigating a live gambling site, fully autonomous, no human in the loop:

we built autonomous AI agents that hunt illegal online gambling networks in Indonesia. the agent discovers sites on its own, actually registers (!!), and extracts the financial accounts behind the operations. take a look at our codex-powered agent navigating a live gambling site, fully autonomous, no human in the loop:

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Google just released a free 2-hour course on full Graph Engineering. How to go from one prompt to 100 agents running inside a single graph: 0% → 17:44 - build your first AI agent 25% → 39:30 - run agents with loop engineering 50% → 1:12:38 - turn agent loops into graphs 75% → 1:34:26 - build agents that regulate themselves 100% → 1:55:05 - orchestrate the entire multi-agent system Most people build one agent and stop there. Google is teaching the entire stack: Prompt → Agents → Loops → Graphs → Multi-Agent Systems Single agents are the old workflow. Self-regulating agent graphs are the next one. This 2-hour course is worth more than most paid agent engineering courses. Bookmark it and watch today Then read the full architecture below ↓

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A 21-YEAR-OLD FROM CHINA RUNS 300 AI AGENTS AT ONCE. THE PART THAT MATTERS ISN'T THE SPEED, IT'S THAT NONE OF THEM CAN LIE TO HIM he opens the dashboard and shows the swarm live, 300 Kimi K2.6 agents firing in parallel, then Opus 4.8 checking every single output against its source. this is not just a faster swarm. it is a loop that refuses to stop while anything is still wrong he pointed it at 100 EV-market companies. first pass: 12 failed. wrong revenue, dead citations, empty fields. second pass: 3 failed. third pass: zero this is not another agent demo. it is a system that catches its own mistakes before he reads a single row

A 21-YEAR-OLD FROM CHINA RUNS 300 AI AGENTS AT ONCE. THE PART THAT MATTERS ISN'T THE SPEED, IT'S THAT NONE OF THEM CAN LIE TO HIM he opens the dashboard and shows the swarm live, 300 Kimi K2.6 agents firing in parallel, then Opus 4.8 checking every single output against its source. this is not just a faster swarm. it is a loop that refuses to stop while anything is still wrong he pointed it at 100 EV-market companies. first pass: 12 failed. wrong revenue, dead citations, empty fields. second pass: 3 failed. third pass: zero this is not another agent demo. it is a system that catches its own mistakes before he reads a single row

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Google just released a free 2-hour course on full Graph Engineering. How to go from one prompt to 100 agents running inside one graph: 17:44 - Build your first AI agent 39:30 - Run agents with loop engineering 1:12:38 - Turn agent loops into graphs 1:34:26 - Build agents that throttle themselves 1:55:05 - Orchestrate the full multi-agent system Most people build one agent and stop there. Google is teaching the full stack: Prompt → Agents → Loops → Graphs → Multi-Agent Systems Single agents are the old workflow. Self-regulating agent graphs are the new one. This 2-hour watch is worth more than most paid agent engineering courses. Bookmark and watch it today Then read the full architecture below ↓

Google just released a free 2-hour course on full Graph Engineering. How to go from one prompt to 100 agents running inside one graph: 17:44 - Build your first AI agent 39:30 - Run agents with loop engineering 1:12:38 - Turn agent loops into graphs 1:34:26 - Build agents that throttle themselves 1:55:05 - Orchestrate the full multi-agent system Most people build one agent and stop there. Google is teaching the full stack: Prompt → Agents → Loops → Graphs → Multi-Agent Systems Single agents are the old workflow. Self-regulating agent graphs are the new one. This 2-hour watch is worth more than most paid agent engineering courses. Bookmark and watch it today Then read the full architecture below ↓

Lunar

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The model sometimes enters a self-critique loop by itself, but you can trigger this manually, and the model tunes the prompt for itself through self-conversation. [Add e.g., "Verify the image, if it's incorrect, write your own prompt, try again, and repeat the process." ]

The model sometimes enters a self-critique loop by itself, but you can trigger this manually, and the model tunes the prompt for itself through self-conversation. [Add e.g., "Verify the image, if it's incorrect, write your own prompt, try again, and repeat the process." ]

Mostafa Dehghani

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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

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Demo 2: human + agent design loop inside Codex. Not every workflow needs the agent to drive everything. You design in Open Design. Codex reviews the output. It can inspect files, open pages, test interactions, critique the design, and turn feedback into the next prompt. Design becomes a human + agent feedback loop.

Demo 2: human + agent design loop inside Codex. Not every workflow needs the agent to drive everything. You design in Open Design. Codex reviews the output. It can inspect files, open pages, test interactions, critique the design, and turn feedback into the next prompt. Design becomes a human + agent feedback loop.

Open Design

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