Agentic coding is a feedback loop
Agentic coding uses AI systems and development tools to work toward a programming goal across multiple steps. The system can inspect a repository, plan changes, run tests and revise its work from the results. That is different from completing a line of code—and it needs a different level of engineering review.
Start with one complete customer outcome
Choose a narrow workflow that a real customer can complete from beginning to end. A smaller, complete release is easier to understand and test than several half-connected features. Define what success means, including the situations where the workflow must stop or ask for human intervention.
Make architecture decisions explicit
Document where business rules live, how records relate and how permissions work before generating features. Prefer the simplest architecture your team can confidently operate. Every extra service adds failure modes, operational responsibilities and maintenance.
Test the boundaries that matter
A passing build is not proof of production readiness. Payments, shared inventory and permissions deserve concrete, independent checks. When an agent writes both code and tests, a person should review the assumptions: the implementation and its tests can share the same mistake.
Release to learn, within limits
Begin with a limited pilot, watch users complete the core task and record where staff must intervene. Establish cost and usage limits. Use observed behaviour to guide the next iteration instead of expanding from the confidence of a polished prototype.
Put the thinking into practice.
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