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8 changes: 4 additions & 4 deletions docs/vision.md
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## The goal

A GitHub organization's repos operate with fully autonomous agents handling the routine software development lifecycle: issue triage, implementation, code review, testing, and merge-to-production. Humans participate at two points:
Everything autonomous is the goal. A GitHub organization's repos operate with agents handling the full software development lifecycle: issue triage, implementation, code review, testing, and merge-to-production. Humans participate at two points:

1. **Strategic intent** β€” defining what the system should do and become. Features, architecture, direction.
2. **Guarded paths** β€” CODEOWNERS-enforced human approval for security-critical, API-changing, or architecturally significant code paths.
2. **Guardrails** β€” CODEOWNERS-enforced human approval for security-critical, API-changing, or architecturally significant code paths.
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Everything else is autonomous.
Getting there is incremental. Each phase and transition in the [agentic SDLC](#the-agentic-sdlc) can be configured β€” per workflow β€” as human-driven, agent-driven, or both. A bugfix workflow might run fully autonomously while a feature workflow keeps a human in the loop at refinement and review. Teams adopt at whatever pace builds confidence, shifting one phase at a time rather than flipping a giant switch.
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## The agentic SDLC

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***Feedback*** ◄─── Monitor ◄─────── Delivery
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**Current (bugfix workflow):** An issue reports a bug (***feedback***). An agent triages, implements a fix (***execution***), and validates it against tests and review (***verification***). Humans set strategic intent and approve guarded paths; everything else is autonomous.
**Current (bugfix workflow):** An issue reports a bug (***feedback***). An agent triages, implements a fix (***execution***), and validates it against tests and review (***verification***). Humans must set strategic intent and approve guardrails; everything else may be fully autonomous based on configuration.

**Planned:** Discovery (identifying what needs work from production signals and tech debt), refinement (scoping and decomposing work), prioritization (ordering the backlog), delivery (merge-to-production with graduated autonomy), and monitor (production observability feeding back into the loop).

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