Planner AgentRaw requirement → Jira
End-to-end planning-layer specification: 12 SOP-grounded stages from raw requirement to Jira issue creation, 17 guardrails, task harnessing, pluggable-vector RAG, and IDE implementation prompts for implementers.
What this reference covers
The Planner Agent is a planning-layer architecture reference for enterprise agentic AI: how a raw requirement becomes structured Jira work with guardrails at every stage. It is the spec I use when a client needs more than a single ReAct loop — a governed pipeline with explicit stages, data contracts, and IDE-ready implementation prompts.
The specification documents twelve SOP-grounded planning stages, seventeen guardrails, task harnessing for long-running work, pluggable-vector RAG for grounded context, and twenty-seven supporting SOP documents. Each stage defines inputs, outputs, failure modes, and the human-in-the-loop checkpoints that keep autonomy bounded in production.
- Stage-by-stage flow from unstructured requirement to Jira issue creation
- Guardrail catalogue with enforcement points and rollback behaviour
- Vector RAG integration patterns and retrieval quality checks
- Task harnessing for multi-step plans that survive tool failures
- IDE implementation prompts for teams shipping in Cursor or Claude Code
Browse the interactive preview below, download the full HTML spec, or read related material on agentic AI consulting, the anatomy of an AI agent, and multi-agent systems. For hands-on training, see the corporate courses or book a discovery call.