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The Decision Log is a chronological record of every action the agent has proposed, joined with the outcome (when measured).

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Why it exists

Without a decision log, the agent (and you) have no idea whether suggestions actually worked. With one, you can:
  • Hold the agent accountable: “You said this would lift downloads — did it?”
  • Spot patterns: “Every metadata change in Q1 helped; nothing in Q3 did.”
  • Onboard new teammates with the full reasoning history.
  • Rebuild trust gradually by promoting auto-approve only on action types with consistent good outcomes.

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Where it lives

A SQL view, cofounder_decision_log, joins:
  • cofounder_actions — the proposal: type, payload, status, timestamps
  • cofounder_memory_episodes — the outcome: summary, before/after metrics

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What you see

Surfaced inline in the briefing under ”📜 Decision Log”:

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API

Response:

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How the agent uses it

The decision log feeds back into the reasoner as memory context. When the agent considers proposing a similar action, it sees:
  • Whether you’ve ignored the same kind of suggestion before
  • What the measured outcome of past attempts was
  • Whether the action type has been net-positive for your app
This is what makes the agent feel like it’s learning over time rather than starting fresh every morning.