You don't start from a blank page. We bring in two libraries, tune them to your product, and hand them over.
How your agent behaves
The behaviors a guidance agent has to get right, each with the checks to test it.
Explore the packs →What your agent can do
The screens your agent opens when talking is not enough, like a plan the user saves or a guided reset.
Explore the tools →What we tune and leave behind
The pack sets the standard. We tune these working parts to your product and hand them over, so quality holds after we step back.
The map of how a user moves through a conversation, where the agent should push, back off, or hand off to a person, and what it should do at each step.
Why it matters
Without it, you improvise behavior prompt by prompt. With it, every change has a place on the map, and you see what it touches before you ship.
A library of scenarios pulled from real conversations, each with a clear definition of a good response, scored every time the product changes.
Why it matters
It turns "did that feel better?" into a number your team can stand behind, and it catches a regression before your users do.
The rules that keep the product inside its lane, including what it will not do, when it declines, and when it tells a user to call a doctor or another professional.
Why it matters
A coaching or care product can do real harm with the wrong answer. These rules decide where it stops, and they hold as you ship and as the model changes.
The working process that turns live usage into a fix you can prove. You watch what happens, find the gap, fix it, score the fix against the evals, then ship it.
Why it matters
Each release ships on evidence, not a hunch. Your release gate catches a change that drops a score and holds it back before it reaches users.
Your method, written down so the product and your team can follow it. The decisions, frameworks, and terms an expert on your team would use.
Why it matters
The agent gives the same answer your best coach would, instead of leaning on whoever wrote the last prompt. You stop depending on the one or two people who carry the method in their heads.
The conversations, outcomes, and user history your product accumulates, including what worked, for whom, and what the advice led to, captured with consent and kept privacy-safe.
Why it matters
A rival with the same model can rebuild documents and tests in time. They cannot rebuild this without your users. Personalization and outcome proof stand on it.
The first call maps which piece your product needs first, and what it takes to make it reliable.
Pressure-test my productExploring · available on request
Before an agent that takes real actions goes live, we rehearse it against a working clone of the systems it will touch. You see what it does, and what it would have changed, in testing instead of in production.
We offer this on request for teams heading into sensitive production environments. It's an exploration, not a committed service.
A golden eval suite at work
A walkthrough with a sample coaching agent. A subtle regression slips through, the evals catch it, and the team fixes and re-scores it before it reaches users.
Vera
Career coach
Live in production
Turns 1-2 · framing the promotion case
9:04 AM
Every coaching session is scored live against the rubric, not spot-checked later.
