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Keep important project decisions in a repository-controlled document, then point both Claude Code and Codex to that shared record. Use CLAUDE.md and AGENTS.md to tell each assistant where the canonical decisions live and how to consult or propose updates. A chat transcript or agent session can provide continuity within a run, but it is not a dependable substitute for reviewed project documentation.
Where should project decisions live?
Put decisions that should survive new sessions in a file the team can review and version with the code. A decision log, architecture decision record (ADR), or clearly marked documentation section can serve as the canonical record. The format is a team choice, not a required Claude Code or Codex convention.
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For each entry, record the date, scope, decision, rationale, and status: current, superseded, or open. This makes it easier for an assistant—and a teammate—to distinguish an active constraint from an old discussion. Link to related architecture documents where useful.
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What belongs in CLAUDE.md and AGENTS.md?
These files are tool-specific instruction entry points, not interchangeable labels. Claude Code documents project guidance in ./CLAUDE.md and personal guidance in ~/.claude/CLAUDE.md; its memory files load at startup. Codex uses AGENTS.md instruction discovery. OpenAI’s migration guide maps repository or workspace guidance to AGENTS.md, while reusable workflows and agent behavior have separate concepts.
| Location or file | Best fit | Scope and persistence |
|---|---|---|
| Repository decision log or ADR | Canonical project decisions | Shared, reviewable, versioned with the repository |
CLAUDE.md |
Instructions for Claude Code, including a pointer to the decision record | Project guidance; Claude Code documentation says project memory loads at startup |
~/.claude/CLAUDE.md |
Personal preferences for Claude Code | User-level, across projects; not the right home for team decisions |
AGENTS.md |
Instructions for Codex, including a pointer to the decision record | Repository guidance discovered according to Codex’s instruction-file rules |
| Conversation or SDK session history | Continuity within a conversation or run | Not, by itself, the canonical record for future project sessions |
Claude Code also supports imports in its instruction files using @path/to/import; Anthropic documents recursive imports up to five hops. Use imports when they make shared or detailed guidance easier to organize, but keep the decision record itself easy for the team to locate.
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How do you set up a shared workflow?
- Create the canonical record. Add a decision log, ADR directory, or comparable document to the repository. Establish how entries are dated, scoped, and marked current, superseded, or open.
- Point Claude Code to it. In the repository’s root
CLAUDE.md, tell Claude Code to consult the canonical record and relevant architecture documents before making changes. Explain how it should propose a decision update. Anthropic’s documentation describes project and personal memory locations and imports: Claude Code memory. - Point Codex to the same record. Add equivalent guidance in the root
AGENTS.md. Tell Codex where the record is and to consult it and propose updates when work changes a project decision. OpenAI’s guide describes Codex instruction discovery for its CLI implementation: Codex Prompting Guide. - Start fresh sessions with an explicit read request. Ask the assistant to read the applicable instruction files, the decision record, and any relevant architecture documentation before acting. This makes the desired context explicit instead of assuming a prior conversation will be available.
- Review proposed changes before recording them. At the end of consequential work, ask the assistant to draft a dated update if a decision changed. A human should check its accuracy and scope before that update becomes canonical.
Why not rely on session history or automatic memory?
Session history and durable project documentation serve different purposes. OpenAI’s SDK documentation distinguishes conversation history associated with an SDK session from sandbox memory carried across later runs. Those mechanisms can help an agent maintain runtime continuity, but they do not replace a version-controlled record that teammates can inspect and correct.
A fresh session may not have the same transcript, runtime state, or account-level memory as the previous one. A project file is more portable: it travels with the repository and can be reviewed in the same workflow as code changes. For SDK-specific designs, see OpenAI’s documentation on sandbox agents and its guide to building reliable agents with memory and compaction.
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How can you verify what an assistant actually loaded?
Claude Code
Use the /memory command to inspect loaded memory files. If expected guidance is missing, check that the file is in the relevant project or user location and that imports point to valid paths. Anthropic recommends keeping memory specific and structured and reviewing it as a project evolves.
Codex
Check the applicable AGENTS.md files for the actual working directory and the Codex version or deployment in use. OpenAI’s prompting guide describes discovery from the global Codex directory and repository path through the current working directory, with later directory guidance taking precedence in that implementation. Do not treat that behavior as a universal guarantee for every Codex product or custom deployment; verify the effective instruction chain in your environment.
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How should the documentation stay trustworthy?
- Keep durable project decisions in the shared, reviewable record; reserve user-level files for personal preferences.
- Give each decision a date, scope, rationale, and clear status so old choices are not mistaken for current ones.
- Update the canonical record when a decision changes; do not leave contradictory copies in assistant-specific files.
- Review instruction files periodically as the repository and tool behavior change.
- Use the installed tool’s effective configuration when an assistant appears to miss guidance, because discovery behavior can vary by version and deployment.
The file-discovery details cited here describe documented behavior, not a promise that every release behaves identically. Anthropic’s linked memory page is localized, and the Codex discovery description is specifically from an OpenAI Cookbook guide for a CLI implementation.
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