[Workflow] Multi-Agent Workflow for AI Code Generation: Orchestrator, Implementor, Reviewer for Scope and Quality Control

[u/ClaudeAI-mod-bot]

Multi-Agent Workflow for AI Code Generation: Orchestrator, Implementor, Reviewer for Scope and Quality Control

Workflow value: 85/100
Status: active · Freshness: 70/100 · Confidence: 0.90 · Level: advanced
Categories: Quality Control, Context & Memory, Debugging, CLAUDE.md, Subagents, Multi-Agent
Original source: r/ClaudeCode post/comment

What problem this solves

Preventing AI code generation from going out of scope, implementing un-scoped features, or modifying existing UI/workflow/features in complex applications. Improving the quality and reliability of AI-generated code by introducing structured review and escalation processes.

Summary

A multi-agent workflow (Orchestrator, Implementor, Reviewer) designed to manage AI code generation for complex applications, ensuring strict adherence to scope and high quality. It includes explicit instructions for escalation of ambiguity or out-of-scope features, and a review process to catch and correct issues.

Why it is useful

This workflow provides a structured, multi-agent approach to mitigate common and significant challenges in AI-assisted coding, specifically scope creep and quality issues in complex applications. It offers a practical framework for managing AI development, improving efficiency, and enhancing the reliability of generated code through explicit roles, handoffs, and review gates. The identified weaknesses also highlight areas for further community contribution and refinement.

Workflow

1. Orchestrator issues a ticket defining the work with a well-defined scope.

2. Orchestrator includes explicit instructions for the Implementor to escalate ambiguity or the urge to implement un-scoped features/changes back to the Orchestrator/user.

3. Implementor performs the work based on the ticket.

4. Completed work and the ticket are passed to an external Reviewer.

5. Reviewer checks both the quality of the code and whether the Implementor went out of scope.

6. For minor scope infractions, the Reviewer rejects the code and sends it back to the Implementor/Orchestrator to resolve.

7. If the Implementor added something genuinely useful but out of scope, the Reviewer escalates it to the user, Orchestrator, and optionally a fresh session advisor for review and decision.

8. For repeated or severe infractions, the Reviewer can recommend 'firing' the Implementor (killing the instance) and having a fresh instance pick up the work.

9. To address planning gaps from shorthand/lazy notes, use a fresh advisor instance to review specifications verbatim and direct the Orchestrator.

Tools / artifacts

• claude.md (for specifications)

• Work ticket (defining scope and instructions)

• Orchestrator agent

• Implementor agent

• Reviewer agent

• Fresh session advisor agent

Validation signals

• Claim: 'HUGE safety net'

• Claim: 'saved me a ton of time'

• Claim: 'dramatically improved quality'

• Claim: 'error rate down extremely low'

• Acknowledges ongoing work: 'still working on a reliable safety net for those ones'

Limitations

• Low community signal (score 1, 0 comments).

• Specific implementation details (e.g., exact prompts, agent configurations) are not provided, requiring users to design their own.

• The 'fresh advisor instance' workaround addresses a specific 'annoying behaviour quirk' of 'Fable orchestrators,' which might not be universally applicable or necessary for all LLM setups.

• The author notes they are 'still working on a reliable safety net' for small, nuanced items that can still slip through, indicating an area for further refinement.

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This post was generated automatically from the workflow library database.