Ralph Wiggum: Autonomous Loops for Claude Code
The official Claude Code plugin that lets agents work autonomously for hours. When to use it, when not to, and the philosophy behind letting AI fail repeatedly until it succeeds.
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The official Claude Code plugin that lets agents work autonomously for hours. When to use it, when not to, and the philosophy behind letting AI fail repeatedly until it succeeds.
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The methodology behind autonomous coding loops. Three phases, five files, and the backpressure that makes it converge.
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Boris Cherny shared his workflow for the tool he built. The setup is surprisingly vanilla. The philosophy is worth studying.
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From diagnosing ad fraud to building a solution. Introducing FameCake: mobile-first billboard booking for everyday moments.
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I wrote that 19-agent scaffolding is a trap. Then Yegge shipped Gas Town with 20-30 Claude Code instances. Are these the same thing?
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Playwright MCP's 26 tools are killing your context window. Vercel's agent-browser shows a better way: fewer tools, smarter snapshots, 93% less overhead.
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Task management designed for AI coding agents. CLI-first, git-native sync, and Model Context Protocol integration.
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A lookup table technique that improves search tool hit rates in autonomous loops. The detail that makes specs discoverable.
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75M monthly downloads. 80% revenue drop. 75% of engineers gone. AI didn't replace developers - it replaced the web as the interface layer. That's worse.
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Anthropic blocked third-party tools from using Claude subscriptions overnight. OpenCode, xAI, and power users caught in the crossfire. The era of subscription arbitrage is over.
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Stanford data confirms experienced devs are safe. But if AI replaces the on-ramp, where do future seniors come from?
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Real footgun stories and the deterministic hooks that would've prevented them. From $30k API key leaks to nuked home directories.
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Skills controllability, hooks limitations, plan mode friction - 2.1 addresses the documented pain points. Here's what changed and what's still missing.
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Complex AI scaffolding tools appeal to people who understand traditional SDLC. But AI collapses the phases that made those models useful.
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The 'prompt engineering' industry was a symptom of early model limitations. Modern LLMs just need you to communicate clearly.
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