---
title: "AICoach: Onboarding that pays for itself by week one. +18 pt activation."
description: "Static onboarding forms were killing AICoach's activation. We replaced them with an adaptive LLM flow that listens to the user's goal, experience, and constraints, and shipped the eval suite the team now owns. +18 percentage points on week-one activation, measured against the previous flow."
source: "https://www.kensink.com/cases/aicoach/"
---
PRODUCT · CONSUMER FITNESS AICoach (US) · US

# AICoach.  
Onboarding that pays for itself by week one.

+18 pt activation.

+18 pt

Week-one activation lift

ONBOARDING + EVAL PRODUCT · CONSUMER FITNESS

## AICoach: Onboarding that pays for itself by week one. +18 pt activation.

Static onboarding forms were killing AICoach's activation. We replaced them with an adaptive LLM flow that listens to the user's goal, experience, and constraints, and shipped the eval suite the team now owns. +18 percentage points on week-one activation, measured against the previous flow.

[View .md](https://www.kensink.com/cases/aicoach.md)

+18 pt

Week-one activation lift

94%

Prompt eval pass rate

< 500 ms

TTFB on streamed first token

8 wk

Kickoff → live in production

01 · THE PROBLEM

## Where they were stuck.

AICoach had a 47% week-one drop-off problem. Users signed up, looked at the empty dashboard, and never came back. The static onboarding form felt clinical and the manually-written coaching prompts didn't adapt to the user's goal, experience, or activity constraints. Activation was stuck below the rate the business model required.

02 · OUR APPROACH

## How we built it.

-   01 Adaptive onboarding: coaching prompts generated from goal + experience + constraints (time, equipment, injuries)
-   02 Streaming LLM responses for perceived speed, with skeleton states the user reads while the response composes
-   03 Edge-deployed AI inference with sub-500ms TTFB worldwide
-   04 Behavior eval suite: prompt-pass-rate across 40 user archetypes, gated in CI
-   05 Observability dashboard the AICoach team uses to spot bad outputs before users do

> “We'd tried two off-the-shelf onboarding tools. Neither moved the needle on activation. The Kensink team scoped the simplest version that could possibly work and shipped it, then handed us the eval suite so we own quality going forward.”

_Product Lead

AICoach_

\[TECH STACK\]

-   TypeScript
-   Edge AI inference
-   Vector store
-   Error monitoring

\[ENGAGEMENT\]

Duration 8 weeks

Client AICoach (US)

Shape ONBOARDING + EVAL

Handoff Full ownership · 90-day warranty

START YOUR OWN PROJECT

## Bring a real problem.  
We’ll bring code on day one.

[Start your own project →](https://www.kensink.com/contact) [Book a 15-min intro](https://www.kensink.com/contact)

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