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Most AI products spend their first screen apologizing for the model.
Disclaimers. "Results may vary." A blank box that hands the user the entire job of figuring out what to type. Then the team wonder why activation is soft.
I design the opposite ; a first turn that does one thing and earns the second.
Three things that I keep coming back to:
*The first turn is the whole product*. If someone hits an error before they hit a real result, they don't come back to give you ae first turn; don't caption it.
*Show uncertainty before it costs trust*. A model that says "here's what I'm sure of, here's what I'd double-check" keeps its credibility through the answer that's wrong. One that's always confident spends trust it can't rebuild.
*Handoff is a feature, not a failure*, The moment the AI reaches its edge and hands off cleanly is where people decide whether to rely on it. Most products treat that moment as something to hide.
None of this shows up in your evals. It shows up in churn.
I made my 5-day audit that looks bookable pay and start, no call required: https://contra.com/yjCLqh6r/p/yjCLqh6r-ux-audit-critical-flow
Happy to disagree in the replies.
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Starting with an original product photo and turning it into a polished e-commerce visual through an AI-assisted workflow.
AI can speed up the production, but it doesn’t replace creative thinking. The creative direction behind the AI still matters; from composition, lighting, environment, and product placement to deciding what actually works for the brand.
These decisions come from human experience: everything we’ve learned, seen, and experienced, combined with our own creative taste and judgment. AI can execute the direction, but we’re still the ones defining it.
Original product photo → e-commerce-ready creative.
Faster production, without removing the human design decisions behind it.
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the red light makes the shot pop
A cinematic website still needs to know when to stop performing.
AERÉ ends the immersive sequence before the enquiry form.
The final job is simple: make the next step obvious and easy.
Experience builds desire.
Conversion design removes friction.
What does AI get wrong when you hand it a real brief?
I gave Kittl's agentic AI a brief we'd already shipped at Formeta, retail packaging for Ella by Ellaya Health, an at-home device for a common pelvic health condition, sold over the counter in Indian pharmacies. Plain language, no steering.
Pass one: four directions, three of them straight to the wellness reflex, lotus marks and sunrise gradients. All four were front faces attached to no box.
Pass two, with panel requirements and regulatory copy, came back with a real dieline. Glue flaps, directions for use, batch and expiry fields. Structurally a genuine leap.
It was also the wrong product. Invented a manufacturing licence number, added a CE mark to something sold only in India, moved the client to a different city.
On direction, Kittl is legitimately useful and I'd use it again. But healthcare packaging is a compliance problem wearing a design problem's clothes, and the model has no way to know it doesn't know that.
Vague brief gets you pretty. Precise brief gets you PLAUSIBLE. Plausible is the more dangerous one, because a founder without a designer might send it to print.
Last slide is the box we built.
Where do you let AI take the first swing, and where do you refuse?
It was super fun to experiment using Kittl with @Ansh Jamdagni 🫶