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Kiberon LabsAgentic Engineering Ebook

Execution and Feedback

Description

Section titled “Description”

The central question in agentic software development is not only which model plans the work, but where the work actually runs and how the system learns whether it succeeded. A credible delivery system needs durable execution records, recurring feedback loops, and explicit human override paths.

Execution As the System of Record

Section titled “Execution As the System of Record”

Local execution is useful during early development. It is fast, cheap, and convenient for prototyping agent behavior, testing prompts, and validating tool harnesses. It is also structurally weak: local runs are hard to audit, difficult to replay, and easy to lose when incidents or disputes require reconstruction.

Long term, execution must move to cloud agents when the goal is production delivery. Cloud execution creates a durable control plane for logs, artifacts, identities, policies, and runtime state. That makes it possible to answer questions such as who invoked the work, which inputs were used, what tools were called, which commits or environments were touched, and why a result was approved or rejected.

This does not mean local execution disappears. Local agents remain valuable as a development tier, a resilience hedge, and a way to experiment without paying cloud costs. The point is that local execution should not be the canonical record for organizational software delivery.

Feedback Cycles

Section titled “Feedback Cycles”

Useful agentic execution depends on layered feedback rather than a single final review.

  • Pre-execution feedback checks whether the issue is clear enough to act on.
  • In-flight feedback evaluates plan quality, test progress, and intermediate artifacts before the agent spends large amounts of time or money.
  • Post-execution feedback covers CI results, code review, product validation, and operational outcomes after deployment.
  • Recursive feedback reopens the same task or follow-on task when review finds defects, ambiguity, or changed requirements.

Human review remains part of the loop even in a highly autonomous system. The role changes from manually doing all work to setting policy, resolving ambiguity, approving high-risk changes, and correcting the system when it drifts.

Human Escape Hatches

Section titled “Human Escape Hatches”

Humans need direct interaction points with active agent work rather than only retrospective review.

  • Pause or cancel a running execution.
  • Inject clarifications, files, or decisions into an active plan.
  • Reassign work from one agent or model class to another.
  • Enter the runtime directly to inspect filesystem state, logs, and intermediate artifacts.
  • Convert a failing autonomous run into a mixed-initiative session without discarding its context.

Escape hatches are not evidence that autonomy failed. They are what make autonomy operationally usable inside real engineering organizations.

Section titled “Related Concepts”