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AI Tooling · Tier 1

Agentic Development Life Cycle (ADLC)

The engineering manifesto that replaced ad-hoc ticket work at my company with a phase-gated, human-approved delivery pipeline.
Role Author & Programme LeadEmployer Polygon Technology LimitedArea AI Tooling
Agentic Development Life Cycle (ADLC) diagram

Problem

Ad-hoc ticket work with no specification gate and no traceability.

Approach

A phase-gated pipeline — proposal, an agent-ready specification, a governance and vetting gate, then an EPIC delivery loop that runs spec, plan, tasks, agent implementation, integration, verification and review to done — with mandatory human approval at every transition, and supervised maintenance and handover after feature complete.

Outcome

Qualitative — multiple teams converted to spec-driven development; every engineer trained in context engineering

Most "AI in the SDLC" stories are about generating code faster. This one is about what has to be true before generation is safe: a proposal, an agent-ready specification, a governance and vetting gate, and a human approving every phase transition. Only then does the EPIC delivery loop run — spec, plan, tasks, agent implementation, integration, verification, review, done — and the work carries on into supervised maintenance and handover once the feature is complete. The generation step is the easy part.

What I did

  • The practice, authored and rolled out org-wide. Proposal → Agent-ready Spec → Governance & Vetting → EPIC Delivery Loop (Spec → Plan → Tasks → Agent Implements → Integrate → Verify → Review → Done) → Feature Complete → Supervised Maintenance → Handover, with human approval at every transition. Trained every engineer in context engineering; multiple teams converted to spec-driven development.

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