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An Agent Context Sprint is a focused way to seed Deepmerge with the workflow knowledge your agents need but your docs usually miss: edge cases, handoffs, judgment calls, customer exceptions, system quirks, and the reasons behind them. Instead of asking people to write documentation, Deepmerge runs short AI-guided interviews, synthesizes the evidence, and turns the results into durable memories your tools can reuse.

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What a sprint produces

Each sprint gives you:
  • A report synthesized from the completed conversations.
  • Findings, decisions, artifacts, insights, and draft skills saved to the workspace.
  • A participant plan and hypotheses, so the report is clear about who was asked and what the sprint tested.
  • A reuse proof task: a concrete agent task that shows whether Claude, ChatGPT, Cursor, or another connected tool can apply the new context.

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When to run one

Run a sprint when a workflow depends on knowledge trapped in people’s heads:
  • Support escalation rules.
  • Refund and exception handling.
  • Fulfillment edge cases.
  • Agency client onboarding.
  • QA handoffs.
  • Any repeatable process where agent mistakes cost time or money.

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How it works

1

Pick one workflow

Choose the workflow where better agent context would save time or reduce errors.
2

Invite the people who know it

Add participants who have first-hand examples. Deepmerge sends personal interview links.
3

Let the AI interviewer gather evidence

Each participant completes a short text or voice conversation. The interviewer searches the workspace during the conversation so questions use what the team already knows.
4

Read the report and reuse the context

As conversations finish, the report is rewritten from the evidence so far. When the sprint is done, use the saved insights and skills in a real agent task.
Context Sprints are available from the Deepmerge dashboard. For the normal agent habit outside a sprint, see the daily workflow.