Give AI a bounded job
A useful AI workflow might summarize an exception, classify an incoming request, or draft a response for review. It should not quietly become the authority for financial commitments, access changes, or operational decisions outside its scope. OpsFoundry separates suggestions from authorized actions.
We first ask whether a deterministic rule or ordinary automation is sufficient. AI is most useful when the task involves variable language or interpretation and there is a practical way to evaluate the output.
Make the controls part of the design
A pilot should define both what the system may do and what must happen when it cannot produce a reliable answer.
- Approved inputs and a policy for sensitive information.
- Representative test cases with expected outcomes and failure examples.
- Source references or supporting evidence where the task requires them.
- Human review before consequential actions, with an edit and reject path.
- Audit records, cost boundaries, fallback steps, and an accountable owner.
Evaluate quality, not just a convincing demo
Measure correction rate, unsupported statements, escalation rate, review time, and end-to-end task completion. Keep some evaluation cases separate from the examples used during development. Repeat the tests when the model, prompt, or source material changes.
Begin with a low-consequence, reversible task. Expand only when the evaluation and operating controls support it. Atlas is one OpsFoundry application that illustrates an emphasis on bounded experiments and recorded decisions; it is not a substitute for validation in your business process.