Where the Agent Development Lifecycle Fits

An AI agent should be treated as a distinct system within the larger application it powers, with its own separate but coordinated development lifecycle (ADLC). This approach allows for independent agent capability development while ensuring alignment with the application's goals. Shared requirements are managed through versioned behavioral contracts and integrated evaluation cases that track the agent's results through the entire application workflow. This structured process uses explicit design investigations and evidence-based readiness assessments to manage complexity and make informed deployment decisions.