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Kayce Basques
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ai/agents/index.rst

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.. _Memory & project docs: https://github.com/openai/codex?tab=readme-ov-file#memory--project-docs
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.. _contextFileName: https://github.com/google-gemini/gemini-cli/blob/3a369ddec3b226dea9d1a9dcc3bae048310edffd/docs/cli/configuration.md?plain=1#L36
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.. _path\:CLAUDE.md: https://github.com/search?q=path%3ACLAUDE.md&type=code
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.. _Gemini CLI: https://github.com/google-gemini/gemini-cli
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.. _Aider: https://aider.chat/
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.. _Windsurf: https://windsurf.com/
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.. _Copilot: https://github.com/features/copilot
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==================
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Docs for AI agents
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we really have to maintain the agent docs and eng docs as separate docs sets?
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This page contains my notes on these questions.
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Scope:
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* I work on *developer* docs i.e. docs for software engineers. I don't know
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how relevant AI agents are for technical writers in other industries or
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domains.
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* I'm thinking specifically about docs for AI *agents*. I'm not
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sure that an all-encompassing "docs for AI best practices" exists. The way
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that we optimize docs for RAG-based chatbots (for example) is probably
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different than the way we optimize docs for AI agents.
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-----------------
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Internal eng docs
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-----------------
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As a software developer, your primary interface for interacting with an AI
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agent is through a chat interface that's been bolted onto your CLI (e.g.
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`Claude Code`_) or IDE (e.g. `Cursor`_). The power of AI agents is their
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`Claude Code`_, `Gemini CLI`_, `Aider`_, etc.) or IDE (e.g. `Cursor`_,
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`Windsurf`_, `Copilot`_, etc.). The power of AI agents is their
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ability to combine LLM capabilities with **tools** like web search and
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``grep``.
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* `Share with your team`_
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* `Memory & project docs`_
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* `Manage Claude's memory`_
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* `Rules`_
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Gotta keep 'em separated?

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