At a glance
What you need to know.
Autonomy should be a bounded permission within a supported workflow. Define the goal, state, allowed tools and stopping rule before creating an agent loop. Treat effects as traceable business operations and verify their destination state. More iterations do not replace authority, evaluation or a safe exception path.
Define one accepted goal and its exclusions
Choose a task with an observable finish, such as preparing a reviewed response draft from approved sources. State which actions and data are outside the task. Decide whether the model really needs to choose steps or whether a deterministic workflow already describes them. A broad instruction to optimize operations cannot provide a useful acceptance rule. Give the task an owner and an exception destination. Autonomy can then be evaluated as a specific choice within a bounded journey instead of an open-ended permission to explore the estate.
Use durable task state outside the prompt
Represent requested, investigating, proposed, awaiting review, executing and completed states as needed by the task. Store a stable reference, source versions and significant decisions under appropriate access. A conversation transcript can help investigation but should not be the only record of progress. Define how a restart resumes work and how cancellation or a changed input invalidates pending steps. Keep uncertain state explicit. If the agent cannot prove completion, it should return a recoverable exception rather than marking the task successful based on its own narrative.
Give the loop time, cost and action limits
Define maximum iterations, execution duration, tool calls and workload admission for the task category. Use bounds that match the operating environment and provider limits. Provide a stop condition for repeated failure or missing authority. A loop that keeps searching or retrying can create cost and queue pressure without improving the result. Store enough progress to explain why the limit was reached. Test a cyclic plan, an irrelevant tool response and a persistent dependency error. Operators need a way to stop pending tasks without losing their recorded status.
Treat tools as controlled business interfaces
Expose the smallest operation that supports the task, with schema validation, record scope and expected errors. Keep credentials on the server and restrict returned data. Validate the current identity for every effect, including actions after a long delay. A tool can report received, pending or accepted; make those meanings explicit. Do not allow arbitrary commands or unrestricted queries because they are convenient during a prototype. Test malformed arguments, a different tenant identifier and an unexpected destination response independently of the model's intended behavior.
Make retry and partial completion deliberate
In an illustrative task, the agent submits an approved record but receives a timeout. The destination may have accepted it. Store the business reference, query or reconcile destination state under the supported contract, and retry only unresolved work. For a multi-step task, distinguish completed effects from reversible proposals and define the recovery owner. Do not let the model invent rollback rules for financial or authoritative records. Bounded retry, duplicate handling and a durable exception path are workflow responsibilities that remain necessary even when the next-step planner changes.
Prove autonomy adds value before expanding it
Compare the agent with a fixed workflow or assisted manual baseline using representative normal, ambiguous and adversarial cases. Measure accepted completions, unwanted effects, reviewer effort, elapsed time and full cost. Include an unavailable tool and stale source. Verify the actual destination record for effectful tasks. Start with one category and record why it may run unattended. A successful demonstration proves that example; production readiness requires task coverage, permissions, operating ownership and recovery that the team can execute without depending on the prototype author.
Keep evidence and execution under separate authority
An AI-generated proposal is not authorization to perform a business action. Validate record ownership, tool arguments and the permitted operation outside the model using the actual requesting identity. Restrict tools to the agreed task and require a reviewed path for privileged or irreversible decisions. Treat retrieved documents and tool responses as untrusted content that can contain misleading instructions. Preserve the evidence a reviewer needs with appropriate access, rather than exposing raw sensitive inputs in general logs. OWASP's prompt-injection guidance supports layered controls; retrieval, fine-tuning and a carefully written prompt do not establish an enforceable security boundary.
Before you start.
- What accepted goal and explicit exclusions bound the task?
- Can state survive restart and changed inputs?
- Are iteration, cost and action limits enforced?
- Does every tool validate authority independently?
- Is ambiguous completion reconciled before retry?
Common questions.
When can a task run without a reviewer?
When its permitted effects, acceptance cases and recovery requirements justify that policy and the organization authorizes it. Establish deterministic controls, bounded execution and evaluated task coverage first. Keep an exception owner and stop mechanism for cases outside the supported category.
Should the agent retry every tool error?
No. A permanent validation failure differs from a temporary outage, and a timeout after a write may conceal success. Use the tool contract, bounded retries and destination reconciliation. Preserve unresolved state for an authorized operator when the result cannot be determined safely.