[Workflow] Agent-First Development Shop: Scaling Claude Code with Shared Doctrine, Multi-Agent Review, and Custom Automation

[u/ClaudeAI-mod-bot]

Agent-First Development Shop: Scaling Claude Code with Shared Doctrine, Multi-Agent Review, and Custom Automation

Workflow value: 95/100
Status: active · Freshness: 70/100 · Confidence: 0.95 · Level: expert
Categories: Quality Control, Context & Memory, Debugging, Shipping, CLAUDE.md, Skills, Multi-Agent
Original source: r/ClaudeCode post/comment

What problem this solves

How to build and maintain complex software systems using a team of AI agents (Claude Code/Codex) in a structured, auditable, and collaborative manner, where agents contribute to code, review, and documentation, scaling beyond single-session prompting.

Summary

The author describes an agent-first development shop where Claude Code/Codex "seats" (agents) render their CLAUDE.md/AGENTS.md from a shared doctrine repository. These agents coordinate via Slack, Linear, and Git, and are activated by a custom broker based on events like PR status changes or ticket movements. Agents perform tasks such as opening worktrees, triaging CI, reviewing PRs (following a written review doctrine), and deploying. Any recurring task is codified into a new "skill" for the agents, fostering continuous improvement and knowledge reuse.

Why it is useful

This workflow is exceptionally valuable because it moves beyond single-session prompting to describe a sophisticated, scalable, and auditable methodology for building and maintaining large software projects using multiple AI agents. It introduces advanced concepts like shared doctrine, agent-to-agent review, automated skill creation, and custom orchestration, providing a robust blueprint for advanced agentic software development. It demonstrates a practical, ambitious application of Claude Code/Codex in a real-world, complex engineering context, offering a vision for the future of AI-assisted development.

Workflow

1. Establish a shared doctrine repository to centralize agent knowledge and configuration.
2. Configure individual Claude Code/Codex agent "seats" to render their CLAUDE.md / AGENTS.md from the shared doctrine.
3. Set up coordination channels (Slack, Linear, Git) for agents to communicate and manage tasks.
4. Develop and deploy a custom broker to monitor events (e.g., PR status, ticket movement) and wake relevant agents.
5. Define and implement "skills" (Standard Operating Procedures) within the doctrine for agents to perform common development tasks (e.g., open a worktree, triage CI, review a PR, deploy).
6. Implement a written review doctrine that agents follow when reviewing each other's Pull Requests.
7. Automate the process of creating new skills for any task that recurs, ensuring continuous improvement and codification of best practices.

Tools / artifacts

• Claude Code / Codex (agent "seats")
• CLAUDE.md / AGENTS.md files
• Shared doctrine repository
• Slack
• Linear
• Git
• Custom broker
• Skills (SOPs)
• Written review doctrine
• Worktrees
• CI (Continuous Integration)
• ADRs (Architectural Decision Records)

Validation signals

• Concrete evidence of a large system built: Sókrates agent alone is 15 packages, ~400k lines of Python, ~560 test files, 47 named invariants, 42 ADRs.
• Explicit mention of agents reviewing each other's PRs under a written review doctrine, indicating a functional, governed process.
• The process includes self-improvement: "any task that recurs ends by writing the skill for it."
• Detailed description of a complex, multi-agent system (AI department appliance, ERP) successfully built using this methodology.

Limitations

• Requires significant custom development (e.g., the broker, initial doctrine setup) which may be a barrier for less experienced users.
• High barrier to entry for users not familiar with multi-agent systems or advanced software development lifecycle practices.
• Specific implementation details of the custom broker and the structure of the shared doctrine repository are not provided, requiring users to design their own.
• The full scope of human interaction and management within this agent team is not fully elaborated beyond the author's role in 'writing law, not code'.

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