Anthropic's agentic workflow — explore, plan, implement, commit — is the right loop for a single coding task, but a delivery project is not a single task. Requirements drift, scope creeps, and one ungoverned suggestion can ripple into a production org. This talk shows how a custom prompt suite can expand those four phases into a governed, story-driven SDLC for Salesforce work: exploration becomes structured discovery and drift checks, planning locks acceptance criteria as the sole authoritative spec, and implementation runs through execution, code review, and QA as distinct gates. The loop still iterates fast — it just can no longer wander or expand scope silently.

For public-sector teams, that governance is the point. Agencies operate under audit, change-control, and accountability mandates an unconstrained loop cannot satisfy. A purpose-built prompt suite answers them structurally: deployments and script runs are logged, drift is checked before execution, and every scope change flows through one auditable channel — producing a defensible paper trail government work demands. Attendees leave understanding how a custom agentic workflow lets AI accelerate Salesforce delivery without surrendering the traceability and control public-sector work requires.