AI-assisted programming needs an evidence trail

Start with an intended use

A useful pilot is deliberately narrow: draft a unit test, explain an unfamiliar function, or propose code against a synthetic specification. Record which inputs are allowed and which decisions remain with a named reviewer. Treat generated code as a candidate implementation. A plausible explanation does not demonstrate that a derivation matches the analysis plan.

Build a reference set before the demonstration

Prepare examples that include awkward cases: missing dates, overlapping intervals, duplicate keys, empty populations and unexpected units. Decide the expected result before asking the model to solve them. Keep development examples separate from the final evaluation set. Repeatedly adapting to the same test set can make an apparently impressive demonstration misleading.

Preserve the decisions around the code

Retain the relevant specification version, model identifier where available, prompt template, approved inputs, generated output, reviewer changes and test results. Avoid logging confidential source data into an unapproved service. Vendor retention, hosting and access arrangements belong in the implementation review, not in a footnote after deployment.

Judge the workflow as well as the answer

Measure escaped errors, reviewer effort and reproducibility alongside time saved. An assistant that produces more code but increases review burden may not improve delivery. Define a fallback when the tool is unavailable or its behaviour changes. Require a fresh evaluation after a material model, prompt or data-source change.

A practical first engagement

Begin with one low-risk workflow and a written evaluation protocol. The deliverable should be a decision: proceed within defined limits, improve the controls, or stop. NIST’s voluntary AI risk framework can help structure that conversation; it is not a certificate that a particular implementation is safe.

Sources & further reading

• NIST — AI Risk Management Framework

Sources checked 20 September 2026. Implementation commentary reflects a practical review perspective; source material may change.