Before
Developers manually handled repetitive setup and cross-file consistency updates.
Dave Chapman
AI, Agents & Automation for Real Business Work
Case study
Agentic development workflow with human checkpoints
Reduced review latency by automating repeatable implementation and verification loops.
Bottleneck -> Boundary -> Build -> Measure
After
Agents complete repetitive coding passes while humans evaluate intent, risk, and release quality.
Decision trace
From friction to measurable outcome
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Problem
Teams lost cycle time to repeatable setup, regression checks, and boilerplate updates.
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Boundary
Agents can propose and implement scoped changes; merge decisions stay human-owned.
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Implementation
Reduced review latency by automating repeatable implementation and verification loops.
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Outcome
Pull request cycle time fell 28% on bounded task classes.
Constraint first
All generated changes require deterministic checks and reviewer approval.
Outcome evidence
Pull request cycle time fell 28% on bounded task classes.
System boundary
Agent software delivery cycle with human review gates
The agent handles scoped implementation work, while human review gates keep accountability, quality, and release confidence explicit.
