Multi-agent software development orchestration pipeline
A software development workflow in which an orchestrator delegates implementation, review, security auditing, and release to specialized AI agents. Agents use separate contexts and, ideally, different model families so that independent reviewers can catch correctness and security problems before code ships.
From DevOps & AI Toolkit — Why One AI Agent Is Never Enough at 00:39
Problem: A single AI agent combines coding and self-assessment, accumulates distracting context, and can ship broken or insecure code. Separate specialist agents provide independent review, security auditing, mechanical release execution, and automatic rework loops.
For: Software engineers, technical leads, architects, and teams that want AI agents to carry features from a PRD to a merged pull request while humans focus on direction, design decisions, and final approvals.
Examples
- Software development workflow: a coder implements a task, a reviewer and auditor inspect it in parallel, and a releaser takes the approved change through CI to a merged pull request.