AI Agent OSGuarded mainnet beta. .rama identity, smart wallets, sponsored gas, permissions and scheduling are available for controlled testing.Open Agent OS
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AI Agent OS

Data Boundaries for AI Agents

Keep private context, transaction intent and public blockchain data separated so an agent has only the information it needs for each task.

In this guide

Practical outcomes

  • Classify data
  • Minimize access
  • Protect sensitive context

How this works in practice

Keep private context, transaction intent and public blockchain data separated so an agent has only the information it needs for each task.

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. Classify data. Define the expected result, capture the relevant onchain or operational evidence, and stop for review if the result differs from the plan.
  2. 02. Minimize access. Define the expected result, capture the relevant onchain or operational evidence, and stop for review if the result differs from the plan.
  3. 03. Protect sensitive context. 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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