The instinct with agents is to make one really capable agent and give it everything. In practice, that agent loses the plot on anything non-trivial — it mixes up what to build, how to build it, and whether it works inside a single context.
Division of labour
When I built Agent SDLC, I split the software lifecycle into specialised agents that each own one role:
- Business Analyst — clarifies and structures the requirement.
- Designer — turns it into a concrete plan.
- Developer — implements against that plan.
- Tester — verifies and feeds issues back.
Each role gets a focused prompt, its own tools, and an explicit definition of "done."
Why this works better
Three reasons:
- Scoped context — each agent reasons about one job, not four. Less to confuse, fewer dropped requirements.
- Inspectable handoffs — you can read what the Analyst produced before the Developer touched it. When something goes wrong, you know which role failed.
- Replaceable parts — improve the Tester without touching the Developer. The pipeline gets better role-by-role instead of all-or-nothing.
A monolithic agent is a black box. A multi-agent graph is a pipeline you can debug.
The orchestration matters
I run these on the GoClaw agentic framework with explicit handoffs and shared state. The framework isn't the point — the point is that structure (clear roles, clear handoffs, clear success criteria) is what turns "a clever prompt" into something reliable.
This pattern generalises far beyond coding: any workflow with distinct stages — research, support triage, content pipelines — benefits from the same decomposition.
Thinking about applying multi-agent orchestration to your workflow? Let's talk.