Your AI feature works. Adoption is where it fails.

I help product teams build AI features that users trust, adopt, and return to. Psychology and behavioral economics, applied where your roadmap meets real human behavior.

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The problem

Shipping AI is easy now. Getting humans to rely on it is the hard part.

Your team can build an AI feature in a sprint. The market has made that clear. What the market keeps proving just as clearly: most of those features stall after launch.

Users try the assistant once and quietly go back to the old workflow. They distrust a correct answer because of how it was delivered. Or they trust a wrong answer far too much, and the error lands on your customer. Leadership sees the usage curve flatten and asks what went wrong.

What went wrong is predictable. Human responses to AI follow patterns that behavioral science has studied for years: how trust forms, how it breaks, when people over-rely, when they reject automation outright. Teams that design for these patterns ship AI that sticks. Teams that ignore them ship demos.

My job is making sure you are in the first group.

The value

A psychologist on your product team, exactly when it matters

AI consultants tend to arrive from the technology side. They optimize models, pipelines, and prompts, and they assume the humans will adapt. My work starts from the opposite end, with the person your product has to win over.

You get three things from working with me

Evidence instead of opinions.

I am a trained psychologist and behavioral economist. I know which research holds up, which findings are folklore, and how to test the difference in your product with your users.

Product fluency.

I work inside product teams. Discovery, research, roadmaps, and delivery are my daily environment, so your PMs and engineers get a partner who speaks their language and respects their constraints.

Adoption you can measure.

Every engagement is scoped around observable user behavior: activation, trust, retention, reliance calibrated to what your AI can actually do. We define the target together and measure against it.

Who I work with

Built for teams that ship

My clients are typically SMB and mid-market software companies where one AI bet matters a great deal, and product leaders inside larger organizations who need their team to get this right. Engagements are scoped to fit both worlds: fast and fixed-price for a single team, structured and repeatable when several teams need the same capability.

If you are a CEO, this is for the product you are betting on. If you lead product, this is for the roadmap item everyone is watching. If you build, this is for the feature you want people to actually use.

How it works

Three steps, zero ceremony

1

We talk.

Thirty minutes, free. You describe what you are building and where it is stuck. I tell you honestly whether I can help.

2

I diagnose.

Most engagements start with the audit. Within two weeks you know where the experience loses users and what to fix first.

3

You decide how far to go.

Some teams run the fixes themselves. Others bring me in to design, research, or train. Every engagement stands on its own, and you stay in control of scope and budget.

Ready to find out why adoption is stalling?

One call. Thirty minutes. You leave with at least one useful observation about your product, whether or not we work together.