What are we working toward?
We believe an agent is only as dependable as the system it runs in. We are working toward a loop that finds the actions an agent can’t undo and proposes their checks, for your team to approve.
Previously in this series, we saw that putting AI agents into production takes both predictability and flexibility. Predictability comes from checks that can’t be skipped, at the points of no return, or PNRs: actions that can’t easily be undone. An agent can reach a PNR by many paths, but every one of them passes through the operating system. That is where OnRails holds the agent.
Today your team finds its PNRs and writes their checks, mostly by hand. That works for one workflow. But as models improve, agents will take on more of a company’s work, and the business rules will have to keep up with them.
We believe an agent is only as dependable as the system it runs in. So we are building a system that does this work with your team. It finds the PNRs in what your agents do, proposes a check for each and holds the agents there. Every run then feeds the next round, which closes the loop. And the loop compounds: each round starts from the PNRs and checks your team approved in the last. Once it runs, your team says what must hold and approves what the system proposes, instead of writing every check by hand.
How would the loop work?
Figure 1 · The loop
Every run feeds the next round, and your team approves what OnRails proposes.
- Your agents run, and OnRails records each run. Every program an agent starts, every file it writes and every connection it opens goes into the run’s record.
- OnRails finds the points of no return. From the record, and from the instructions your team already writes, such as AGENTS.md, it proposes the actions that can’t easily be undone. A payment applied, an email sent and a balance written off are such actions.
- OnRails proposes a check for each. It starts from the checks your team already runs, such as a script that verifies the invoice matches.
- Your team approves. A person reviews each PNR and its check before it holds, so the business rules stay your team’s.
- OnRails holds the agents, and the next round begins. Every refusal goes into the record with its reason. From there, OnRails proposes sharper checks, and new PNRs as better models take on new work.
Agents bring the intelligence. OnRails brings the guarantees.
If you’re still making your agents follow a workflow, we’d love to work with you. Email us at [email protected].