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docs: credit HumanLayer in RPI tutorial (#6365)

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Angie Jones
2026-01-06 17:06:29 -06:00
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@@ -10,7 +10,7 @@ import planDoc from '../../static/files/thoughts/plans/2025-12-23-remove-tool-se
Most people use AI agents by jumping straight to execution: "refactor this code", "remove this feature", "add this new feature". While sometimes this works well, especially for smaller changes or codebases, it often falls apart on complex changes. Most people use AI agents by jumping straight to execution: "refactor this code", "remove this feature", "add this new feature". While sometimes this works well, especially for smaller changes or codebases, it often falls apart on complex changes.
**RPI (Research, Plan, Implement)** is a mental model that proposes a different way of working with AI agents. This approach trades speed for clarity, predictability, and correctness. **[RPI (Research, Plan, Implement)](https://github.com/humanlayer/advanced-context-engineering-for-coding-agents/blob/main/ace-fca.md)**, introduced by HumanLayer, proposes a different way of working with AI agents. This approach trades speed for clarity, predictability, and correctness.
This tutorial walks through how RPI works via a real demonstration. By the end, you should be able to run this same workflow on your own codebase. This tutorial walks through how RPI works via a real demonstration. By the end, you should be able to run this same workflow on your own codebase.