Structured Azure DevOps Work Items Matter More Than Your Choice of AI Agent

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A developer advocate argues that the success of AI-assisted Power Platform development depends not on which AI agent is used, but on how well Azure DevOps work items are written. Vaguely worded requirements force agents to guess at intent, producing inconsistent results that are costly to fix later in the development cycle. The author recommends structuring work items with Gherkin-format acceptance criteria, fenced YAML for data schemas, and explicit business rules so that any AI agent can parse them reliably. Using a consistent work item template ensures agents locate structured information in predictable locations rather than interpreting free-form text. This approach makes the specification the stable input contract, allowing teams to swap AI tools without losing reproducibility or auditability.

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