AI-Generated Code: Requirements, Tests and Accountable Review

Reviewed and updated October 8, 2026.

Generated code should enter the same acceptance process as other proposed changes. Decide what the change must do, how it will be checked and who owns its release. The amount of code an agent produces is less useful than a reviewable change that meets the requirements.

An agent can inspect a repository, propose an implementation and run checks. It still needs bounded tool permissions and an accountable reviewer. OWASP's secure coding with AI guidance calls for inspecting generated changes and controlling the execution environment.

Write acceptance before generation

Define the user behavior, inputs, output and exceptions. Identify the data and files the task may touch. State whether the agent can add dependencies, alter tests, access external services or run migrations. Keep credentials and production access outside a default development task.

Choose checks that distinguish correct behavior from a plausible implementation. Existing tests can establish regressions; new tests should encode the requirement rather than merely confirm the generated code. Review test changes with the implementation so a weakened assertion cannot hide a defect.

An illustrative export change

Suppose an agent adds a CSV export of records visible to the signed-in user. This is a worked acceptance example, not a report of an ALLTIPLY code release.

The requirement is to export the user's authorized records with the selected columns and filters. Test a normal export, no matching records, a record in another tenant and an interrupted request. Review the authorization path in the backend. A working download button and a test using an administrator fixture do not establish the intended access boundary.

Inspect the full diff for unrelated dependency changes, modified access rules and altered tests. Check handling of fields that contain separators, quotes or newlines. Confirm that the output does not include internal fields that the screen hides. The reviewer should be able to connect each change to the requested behavior.

Keep review and release controls explicit

NIST SSDF 1.1 includes code review or analysis and security testing as development practices. These checks are relevant whether a person or a model drafts the code. They reduce particular risks without proving that all defects are absent.

GitHub branch protections can require reviews and status checks. Configure the actual repository rules and inspect bypass permissions rather than assuming a green interface implies every required check ran.

Choose where automation is useful

A small, well-specified change can be a good candidate for assisted implementation. Ambiguous requirements, unknown data boundaries or an irreversible migration need investigation and an explicit decision before execution. Break a large request into reviewable changes with their own acceptance evidence.

Keep the change owner, released revision and rollback or recovery approach recorded. For product launch gates beyond code acceptance, read prototype to production AI.

See ALLTIPLY's AI development scope. Request a project review with the desired behavior, existing system and checks that would make the change acceptable.