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Field notes / AI operations

Operate AI workflows as production systems

AI operations covers the work after a prototype succeeds: monitoring, access, evaluation, incident handling, and change management. A workflow is production-ready only when someone can understand and recover it.

YOUR NEXT STEPCHOOSE A GOAL
What would be useful next?

Define the operating contract

State the task, expected inputs, supported outputs, authorized actions, and service dependencies. Decide what happens when data is incomplete or a model cannot produce an acceptable result. Assign…

  1. 01 / Establish the context
  2. 02 / Review the right fit
  3. 03 / Take the next step

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01

Define the operating contract

State the task, expected inputs, supported outputs, authorized actions, and service dependencies. Decide what happens when data is incomplete or a model cannot produce an acceptable result. Assign responsibility for reviewing exceptions and responding to incidents. A workflow that always reports success hides risk and makes later troubleshooting unnecessarily difficult.

  • ✓ Define useful success and failure states.
  • ✓ Keep a manual fallback for business-critical steps.
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02

Monitor decisions and execution separately

A correct recommendation can fail during tool execution; a successful API response can carry an incorrect change. Capture both kinds of evidence with appropriate privacy controls. Measure retries, rejected actions, reviewer overrides, and downstream errors. Use stable identifiers so one task can be traced across the model, application, and external service without storing excessive personal information.

  • ✓ Alert on actionable failures rather than every routine event.
  • ✓ Reconcile external state before retrying a potentially completed write.
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03

Release changes with an evaluation record

Version prompts, policies, schemas, and tool contracts alongside code. Test representative cases before a change and review failures afterward. Keep rollback instructions and verify that prior permissions remain appropriate. Search Intel OS can explain HGM’s orchestration approach; the production boundary and implemented components should be documented for each actual deployment.

  • ✓ Review model and vendor changes as operational changes.
  • ✓ Track maintenance effort and business quality alongside runtime cost.
Managed Agent Operations

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