Engineering leadership
How do I give AI coding agents the right product context?
Give the agent the smallest complete context chain for its task. That usually includes the ticket, its parent project, the user and problem that project serves, the intended outcome, constraints, and current decisions.
Prefer a connected work packet
Large document dumps increase retrieval noise and hide authority. A useful work packet selects current facts and preserves the links that explain why each fact matters.
The agent should be able to move from a ticket to its project, from the project to the persona it serves and the problem it addresses, and from the project to the goal and strategy. Tickets inherit the persona and problem from their project. Missing links must remain visible as missing context.
Scope
Include the files, symbols, interfaces, and non-goals that bound the change.
Product intent
Include the user, problem, outcome, and accepted behavior behind the task.
Authority
Distinguish ratified decisions from drafts, proposals, and historical material.
Keep context live
Load context when work begins and refresh it when the agent prepares the pull request. Context copied into a prompt becomes stale as soon as the source decision changes.
Helen's Foundry exposes the context chain through MCP, so connected agents can read current artifacts and relationships instead of reconstructing intent from scattered tools.
Verify completeness
For user-facing work, require an active persona and problem. For implementation, require testable specifications and any exact code contracts. If those facts are absent, the honest result is blocked context, not agent guesswork.