After Your First Ralph Workflow Run

Ralph Workflow is a free and open-source AI agent orchestrator built around a simple core loop inspired by the original Ralph loop. That simple core composes into a stronger workflow system for serious repo work, and the default workflow is already strong enough to start with before you customize anything.

If Ralph Workflow did its job, the question after your first run is not whether the agent sounded smart.

It is this:

does the implementation hold up?

This page is the shortest path from a private first run to a useful public next step on Codeberg.

Use Codeberg for the real project relationship: stars, watches, issues, and contribution history.

The only branch that matters

Treat the first run as a fork with only two healthy outcomes:

  1. It earned trust → star or watch Ralph Workflow on Codeberg.

  2. It exposed friction → open the matching first-run or docs/proof issue form on Codeberg.

If you do neither, the adoption signal stays private and the project learns nothing.

The two-minute scorecard

After the run finishes, check these in order:

  1. Does the diff match the task?

  2. Did the software actually do the requested thing?

  3. Did the checks actually run, including integration checks where they matter?

  4. Are the changes reviewable in one sitting?

  5. Are open questions called out clearly?

  6. does the implementation hold up?

If the answer to most of these is yes, Ralph Workflow is doing useful work.

If the answer is no, the failure is still useful if you can say why.

What to do next on Codeberg

If the run was genuinely promising

Use the primary repo on Codeberg:

That is the cleanest public signal that Ralph Workflow earned a place in your toolset.

If the run exposed friction

Report it on Codeberg so the fix lands on the primary repo:

Best bug reports say:

  • what real task you tried to hand off

  • where the friction showed up

  • what you expected instead

  • what would have made you more likely to trust or keep using Ralph Workflow

What counts as a successful first run

A successful first run does not need to be perfect.

It only needs to prove something real:

  • the task was scoped well enough to hand off

  • the workflow came back with real executable proof

  • you can tell why you would or would not merge it

That is already much better than a transcript that only sounds finished.

When to give it a harder second task

Move to a bigger second task only if the first run gave you:

  • working behavior you can verify

  • real checks

  • a clean re-entry point the next morning

  • enough trust that you would review another result

If not, do not jump to a bigger task yet.

Instead:

  1. tighten the spec

  2. choose a more bounded task

  3. report the friction on Codeberg

If you are still unsure

Use these in order:

  1. Example review bundle

  2. How to review AI coding output before you merge

  3. Contributing on the primary repo

The goal is simple: convert your first run into one honest public action on Codeberg — either a star/watch because it worked, or a useful issue because it did not.