Blog/Bench
What a bench is, and why every tool gets one
A fixed set of real cases with a written right answer, re-run every month. It's not clever. That's the point.
1 min read · · Boring Agents
- 1A demo shows a tool can succeed once. A bench shows how often it fails.
- 2Cases come from your own queue, messy ones included, never from made-up prompts.
- 3The monthly scorecard goes to you, with the failures listed, not just the score.
Every AI tool looks good in a meeting room. The meeting room is not where it works. It works in an inbox at 6:40 pm on a Friday, next to a customer who wrote half the message in another language and attached the wrong file.
So before we build, we collect a few hundred real cases from the work we're about to automate. Each one gets a written right answer that someone on the client's team agrees with. If nobody can agree what right looks like, that's the most useful thing we'll learn, and it's better learned before anyone has spent money.
That set is the bench. We run the tool against it before it goes live, every month after, and every time the model underneath changes, which happens more often than anyone admits. The result is a score, a trend, and a list of the cases it got wrong.
It's boring on purpose. A boring, repeatable measurement is the only kind you can hold someone to.
Tell us the job your team hates. We'll tell you if AI can do it.
A 30-minute call with the people who would build it. No technical knowledge needed: just describe the job, how often it happens, and how you check it's done right.