Govern coding agents without slowing useful work.

AI coding agent governance is the system of boundaries, evidence, and review that keeps autonomous code changes aligned with the software people remain responsible for.

A prompt is not a governance boundary.

Instructions inside a prompt help an agent reason, but the same agent can reinterpret them when the task expands. Governance needs to live outside that reasoning loop. It should decide what context is available, which files may change, which commands may run, and what evidence is required before a result is accepted.

Kaplira turns each run into an explicit contract. The coding agent still chooses the implementation, while the project controls the area it can affect and the checks it must satisfy.

  • Scope the run to concrete files and architecture blocks
  • Carry known risks and prior decisions into the working context
  • Require validation that matches the affected product flow
  • Retain an inspectable record after the coding session ends

Governance should change what the agent can do.

A dashboard that only reports activity after the fact is observability, not control. Effective governance can stop an undeclared scope expansion, block work that lacks a required plan, or require fresh evidence when an agent repeats an unsuccessful approach.

Those interventions should be attributable. A reviewer needs to see the condition, the policy that applied, the evidence used, and whether any source change reached the repository.

The result is a better next run.

A governed run produces more than a diff. Its accepted decisions, validations, known errors, and unresolved risks become reusable project knowledge. Future agents can begin with the constraints the team has already learned instead of rediscovering them from scratch.