AI & Machine Learning

Your agent context needs a development lifecycle

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Patrick introduces the Context Development Lifecycle (CDLC) to manage AI agent contexts as software, addressing issues like outdated skills and untested configurations. This framework includes phases for generating, evaluating, distributing, and observing context artifacts, ensuring quality and reliability in AI-assisted development.

Teams should adopt CDLC practices to prevent common failures such as broken skills after model updates or incorrect triggers, by implementing rigorous testing and observability measures.

Read the full article at The New Stack

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