Operate dynamic agent plans with bounded execution

A dynamic agent chooses its next action from the results of previous actions. It may inspect a failure, request another dataset slice, or revise a proposed fix instead of following one predetermined sequence.

That flexibility does not require an open-ended execution policy. Use an application-owned controller to manage the plan, and Polyaxon workloads to perform and record authorized work.

Separate a changing plan from stable policy

The model may choose among permitted operations. It should not choose its own credentials, unrestricted data sources, or maximum budget.

For a regression-investigation agent, the allowed actions might include reading a sanitized failure bundle, running a fixed comparison, and evaluating a candidate patch. Deployment remains a separately approved operation.

Store the plan revision and reason for each transition. A useful execution history should explain why the agent changed direction after receiving a result.

Represent progress as durable application state

A controller can maintain states such as proposed, authorized, submitted, running, evaluated, and stopped. Persist the request identifier and associated Polyaxon run UUID at each dispatch.

Do not keep the only copy of progress in a model conversation or a service's memory. After a restart, the controller must determine which work already exists before submitting more.

The RunClient can create and inspect workloads. Your application supplies the state machine and reconciliation rules.

Enforce a cumulative execution budget

A per-command timeout does not bound an agent that can issue unlimited commands. Track the total number of steps, elapsed time, model usage, and resource consumption allowed for one request.

A policy record might look like this:

{
  "max_steps": 12,
  "max_parallel_tasks": 2,
  "max_request_seconds": 900,
  "allowed_operations": [
    "inspect_failure_bundle",
    "compare_metrics",
    "evaluate_patch"
  ],
  "deployment_requires_approval": true
}

This is an application-owned contract, not a Polyaxon configuration schema. Implement the counters and checks in trusted controller code.

Combine it with workload termination and available queue controls to bound individual runs and shared capacity.

Evaluate observations before replanning

Tool output is data. An error message or retrieved document can contain suggested instructions, but it should not expand the controller's authority.

Check process outcome, output completeness, and expected schema before returning an observation to the planner. For generated changes, use an independent evaluator with fixed criteria.

Record useful metrics and reports with Polyaxon tracking. Preserve unsuccessful attempts so later analysis does not overestimate the agent's reliability.

Stop with an informative result

Define normal stopping conditions: the objective is verified, the budget is exhausted, authorization is missing, or repeated attempts are not producing useful progress.

Return the evidence gathered and the unresolved question. A bounded partial result is more useful than an agent that continues consuming resources while repeating the same failed action.

Dynamic planning then becomes a controlled application behavior. Polyaxon provides execution and evidence, while stable policy keeps a changing plan within an understandable operating envelope.