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@@ -23,20 +23,68 @@ Every AI framework has its own structure. There's no universal, portable way to
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## Patterns
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Four architectural patterns emerge when you treat agents as git repos:
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These are the architectural patterns that emerge when you define agents as git-native file systems.
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### Human-in-the-Loop for RL Agents
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When an agent updates memory or learns a new skill, it creates a branch + PR for human review before merging to main. Git's review workflow becomes your supervision layer.
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When an agent learns a new skill or writes to memory, it opens a branch + PR for human review before merging.
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### Shared Context
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Root-level `context.md`, `skills/`, `tools/`, and `knowledge/` are automatically inherited by all sub-agents. One source of truth, no duplication.
The `memory/` folder holds a `runtime/` subfolder where agents write live knowledge — `dailylog.md`, `key-decisions.md`, and `context.md` — persisting state across sessions.
Run `gitagent validate` on every push via GitHub Actions. Test agent behavior in CI, block bad merges, and auto-deploy — treat agent quality like code quality.
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<imgsrc="patterns/ci-cd-agents.png"alt="CI/CD for Agents"width="600" />
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### Agent Diff & Audit Trail
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`git diff` shows exactly what changed between agent versions. `git blame` traces every line to who wrote it and when — full traceability out of the box.
Agent tools that need API keys read from a local `.env` file — kept out of version control via `.gitignore`. Agent config is shareable, secrets stay local.
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