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AI Agent OS

Treasury Controls for AI Agent Operations

Set transparent budgets, withdrawal boundaries and approval policies before assigning treasury-adjacent work to an agent.

In this guide

Practical outcomes

  • Set treasury roles
  • Configure budgets
  • Audit fund movements

How this works in practice

Set transparent budgets, withdrawal boundaries and approval policies before assigning treasury-adjacent work to an agent.

A controlled agent separates the controller from the runtime. The controller owns the agent identity and defines policy, while a smart wallet, permission rules, quotas, relayer and scheduler constrain what the runtime can actually execute.

Implementation sequence

Turn the topic into a controlled implementation rather than a one-off transaction. Each step below should leave evidence a teammate, user or auditor can independently review.

  1. 01. Set treasury roles. Define the expected result, capture the relevant onchain or operational evidence, and stop for review if the result differs from the plan.
  2. 02. Configure budgets. Define the expected result, capture the relevant onchain or operational evidence, and stop for review if the result differs from the plan.
  3. 03. Audit fund movements. Define the expected result, capture the relevant onchain or operational evidence, and stop for review if the result differs from the plan.

Evidence to retain

Record the .rama identity, controller, wallet, policy version, approval event, task identifier and resulting transaction hash. This makes a decision traceable without giving the agent unrestricted custody.

Control point

Start with small allocations, explicit recipient and contract allowlists, bounded session keys and a tested pause path. An automated workflow must never be the only place where authority or recovery knowledge exists.

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