Your agent context needs a development lifecycle

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Skills, agent configurations, prompt instructions, and rules files. These artifacts now determine what your coding agents produce. They shape every line of generated code, every architectural decision, every convention the agent follows or ignores. They are, functionally, software.

Nobody treats them that way. Teams write a skill, commit it to a repo, and never test whether it still works after a model update. Agent configurations are copied and pasted across teams without versioning. Rules files drift out of sync with the codebase they describe. When something breaks, the signal is a developer noticing weird output and complaining on Slack.

“If context is the new code, what is its software development lifecycle?”

Patrick coined a framework for what’s missing: the Context Development Lifecycle. The CDLC is not about context window management or fitting more tokens into a prompt. It’s about managing the quality of the pieces that go into the context window. Is a skill up to date? Does the model actually react to it correctly? Are you providing context the model already knows? If context is the new code, what is its software development lifecycle?

The four phases of the context development lifecycle

The CDLC has four phases that map directly onto what we already do with code.

Generate is where everyone starts. Writing skills, building prompt configurations, setting up agent rules. It’s the equivalent of writing code, and it’s where most of the time goes today.

Evaluate is testing. Checking whether the linting on the front matter is correct or whether the syntax is too …

Vollständiger Originalartikel ↗

• Betroffenheit im eigenen Stack prüfen: Versionen/Komponenten abgleichen.
• Originalquelle / Hersteller-Advisory lesen: https://thenewstack.io/agent-context-development-lifecycle/
• Verfügbaren Patch oder Workaround einspielen und dokumentieren.