AI Agent Systems
AI Agent Build Workflow

Business Context + Approach
Business Context
The team needed faster implementation cycles without losing control, traceability, or quality in production-facing changes.
Approach
- Used task-scoped agent loops for implementation + verification.
- Required evidence and command logs for each major change.
- Maintained human review over risky or deployment-sensitive actions.
Execution Notes
The result is a repeatable pattern for delivering changes quickly while keeping auditability intact.
Outcomes
- Faster turnaround on scoped engineering tasks
- Improved traceability from request to deployment
- Better consistency in documentation and verification
Implementation Snippet
for task in roadmap:
run_tests(task.scope)
apply_patch(task.diff)
capture_evidence(task.id)
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