Peter Werry compares coding agents with employees who are repeatedly onboarded without enough organizational memory. Repository instructions, skills and MCP tools can help, but an agent may still stop at the first plausible answer because it does not know which architectural decisions, prior discussions or future plans matter to the task.
He describes a context engine that connects code with pull requests, Slack conversations, documents and team expertise. In a live planning comparison, the context-aware agent found proposals and architecture details that the baseline plan missed, producing a more specific implementation path with fewer investigative steps.
Werry also shows how the same organizational context can support code review and regression diagnosis. One example links a behavioral change after a model switch to earlier team discussion and then generates a corrective pull request. Promotional calls to sign up, scan a simulator code and attend another talk are omitted.
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