Giving an AI agent access to capital should never mean giving it unlimited authority. The real challenge is not whether an agent can execute a profitable strategy. It is whether the system can keep that agent within clearly defined boundaries when market conditions change or an unexpected decision occurs. That is where @termix_ai takes an important approach with AACP. Protocol whitelists define where an agent can operate. Position limits restrict how much exposure it can take. Independent price references from Chainlink and TWAP help check vault valuations, with a maximum permitted deviation of 5% according to the stated safeguards. For larger vaults, block level keeper execution adds another layer to stop loss protection, reducing dependence on someone noticing a problem and reacting manually. There is also an accountability angle. Keeping provider transactions onchain creates an evidence trail that can help investigators examine suspicious execution patterns, including potential front running. What matters here is the separation between permission and responsibility. An agent may be capable of making decisions, but the infrastructure should still determine what it is allowed to do, how its actions are monitored, and what evidence remains afterward. That is the standard I would look for before trusting automated systems with meaningful capital. Autonomy is useful. Bounded autonomy is what makes it worth considering. Which matters more to you: restricting an agent before execution or being able to audit its actions afterward?