Who it’s for
You ran out of engineers before you ran out of customers.
If a person still reads every response, you already have a correctness graph. It lives in their head, and it doesn't scale.
Agents in production at a typical agent company, each customized per customer.
Steps in a real workflow. Deep enough that context gets squeezed out before the end.
Cost of a single run. Multiply by daily volume before calling this a small problem.
The fit
Three conditions. You need all three.
- Scale. Thousands of executions a day — too many to read, enough for clusters to mean something.
- Customization. Agents differ per customer and per edge case.
- Consequence. A wrong answer reaches a customer or moves money.
Depth matters more than volume. The failures we catch live past step twenty, where nothing has thrown an error.
Where we see it
Same pattern, different industries.
Depth breaks the model
25–40+ step workflows where frontier models degrade, and most calls never needed frontier.
Every upgrade is a rewrite
Prompts re-tuned per model, by hand, breaking as upgrades outrun headcount.
Drift, not crashes
Comfortable switching models, never confident about drift around step forty.
Consequence is immediate
A confidently wrong answer is an operational event, not a support ticket.
Send us one week of past runs.
We'll come back with what your successful executions have in common, the few that stopped matching, and what we think changed. If we find nothing, we'll tell you that too.
Start a design partner conversation