ORBIOOM / WORKFLOWStart with a concrete outcome
Avoid asking an agent to “improve the codebase.” Name the user-facing or technical outcome instead: reproduce a bug, add a small capability, make a screen responsive, explain a failing test, or prepare a focused refactor. A clear outcome gives the work a finish line.
It also makes review easier. You can compare the resulting change against the original intent rather than judging a large, vague set of edits.
Give it the constraints that matter
Relevant constraints are often more valuable than a long prompt. Tell the agent which part of the product is in scope, what must remain unchanged, which checks matter, and what good looks like. This keeps investigation proportionate and protects the work around it.
The same principle applies to product context. A short explanation of the user, the interface, or the team's conventions can prevent a technically correct change from becoming the wrong product decision.
Review the reasoning and the result
Review is not an afterthought. Ask the agent to summarize what it changed, what it verified, and where uncertainty remains. Read the diff, run the relevant checks, and make sure the result preserves the product's standards—not only its syntax.
Over time, this creates a healthier workflow: the agent accelerates the work, while the team remains accountable for what enters the product.
TakeawayThe best AI coding-agent workflow is specific, scoped, and reviewable. Give the agent a real job, then keep judgment close to the result.