The Practical Case for Context Engineering in Software Teams
Someone asked me for a practical example of context engineering.
Here is one pattern I use: keep a separate context layer for product memory, and give agents clear rules for maintaining it.
This is different from putting another AGENTS.md into the product codebase. In this pattern, the context layer may live in a separate repository, an Obsidian-like folder, Confluence, or another internal knowledge base. It is not the source code. It is the structured memory around the product: pages, workflows, API behavior, business rules, incidents, and decisions.
The goal is not to give an agent more text. The goal is to give it the right shape of context.
Why Project Context Comes Before Agent Work
Most AI workflows start too late:
Here is the task. Inspect the repo and figure it out.
Sometimes this works. Often it guesses.
The better starting point is the context layer around the product. That...
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