Outcomes · For engineering teams
Agents that finish the job after a failure
When a worker dies mid-run, the agent resumes where it stopped and reuses the steps it already completed.
Who it is for
Who this is for
Engineering teams running multi-step agent workflows that wait on approvals, background jobs or flaky providers.
What changes
Before and after
Before
- A crashed run starts again from the beginning, or is abandoned.
- Restarting repeats work that already happened, including customer updates.
- A timeout is treated as a failure, and the write is sent twice.
After
- Each step's result is saved, along with the step that should run next.
- A replacement worker restarts with the same run ID, reuses the completed work and continues.
- Progress survives approval waits, background jobs and crashes.
How it is delivered
Delivered by a product, not a project
Delivered by Romulus, through an API and a JavaScript SDK.
- Execute the next step, checkpoint its result, wait or be interrupted, then resume.
- The API runs locally and keeps its state in SQLite.
What you provide
What we need from you
- Node.js 24 to run the preview.
- A workflow you can express as steps with a result worth saving.
- Idempotency or reconciliation for your external writes.
How the result is measured
How you will know it worked
- Run the quickstart: it kills a worker mid-step, restarts it and lets you inspect the recovered run in SQLite.
- For your own workflow, check that completed steps are not repeated after a forced crash.
How to start
How to start
Romulus runs on your machine today. There is no hosted service and no account to create.
Good to know
Limits, stated plainly
- Completed steps are reused. Unfinished work may run again, so external writes still need idempotency or reconciliation.
- A timeout does not mean a write failed: check the original operation with the provider before retrying.
- This is a development preview that runs locally, not a hosted production service.
For engineering teams
Other outcomes
- Agents safe to put into productionEvery tool call your agent makes is checked against permissions before it runs, and the actions that matter wait for a person.
- Lower model cost without losing accuracyA smaller open model is fine-tuned on your own examples and measured against your current model, so you switch only if it holds up.
- Agent workloads kept in the UKYour agents' compute and run records are planned to live in a UK region, so you can say where they are.