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Software teams have no shortage of tools that can suggest code. The harder problem is carrying a task from intent to a change an engineer can confidently review. KeplerCrew is built for that complete path.

What KeplerCrew does

You give KeplerCrew a project, a clear outcome, and constraints. Its workflow spans Discover, Plan, Build, Verify, and Deliver. Permissions, execution boundaries, model connectivity, and checks depend on the configured environment and task.

• Scoped execution — The requested outcome and boundaries stay attached to the job.
• Repository-aware work — Existing conventions, dependencies, and tests guide the implementation.
• Evidence at handoff — Inspect recorded activity, tool results, and artifacts to understand what happened.

Autonomy needs boundaries

KeplerCrew is designed to do substantial engineering work independently, but autonomy is not the same as unchecked access. Branch policy, runtime limits, verification commands, and human review remain explicit controls.

Our goal is straightforward: reduce the time between a well-defined task and a trustworthy implementation while keeping the engineering process visible.

Autonomous development should be evaluated as a system, not as a single model response. The useful unit of work is the job: an isolated run with an explicit objective, known constraints, and a measurable completion contract.

The job lifecycle

• Discover — Read the task, repository structure, relevant files, and project instructions.
• Plan — Convert the request into concrete edits and identify risks before changing code.
• Build — Implement the change in the context of the project.
• Verify — Run the repository's tests, linting, type checks, builds, or task-specific commands.
• Deliver — Bring the result and its evidence back for delivery.

task + constraints + verify commands
                ↓
Discover → Plan → Build → Verify → Deliver
                ↓
diff + command output + review summary

Failure is part of the loop

A run may stop, fail, or need review. Inspect its recorded state and evidence before deciding what to do next. Co-pilot review points help keep human decisions inside the workflow; they do not guarantee that every task will succeed.

This is the practical difference between code generation and autonomous delivery: the output is judged against the repository's actual definition of working software.

KeplerCrew's June preview update strengthens the surfaces around the autonomous pipeline. The execution engine matters, but teams also need a clear way to describe work and understand exactly what happened during a run.

What's included

• Reusable Powers — Expert systems for testing, documentation, refactoring, and code-quality work.
• Verification-first quickstart — Documentation that treats success commands as part of the task, not an afterthought.
• Job visibility — A consistent path from submitted work to status, logs, result, and reviewable artifacts.
• Public product resources — New documentation, status, help, blog, and changelog pages.

What we're improving next

We are continuing to tighten task specification, failure reporting, and repository-specific verification. The standard remains the same: KeplerCrew should show enough evidence for an engineer to understand the change without reconstructing the run.