Founding Designer · AI Products
Your model is right. Your users still won't bet on it.
The half-second of doubt is the only thing I design. Fifteen years, five industries, one problem.
Where does your AI product lose people?
You said
See how I fixed itThe receipts — four industries
What the design was worth.
Who you'd be hiring
Arpit Maheshwari
By Friday of week one I've read your evals and sat in on your customer calls; by launch, the interface I drew is the code I shipped. Fully remote from Indore — 4–5 working hours shared with US East every day.
I read the model at the eval layer. I shape what gets measured. I ship the front-end.
On my first accessibility project I spent a week with my monitor switched off, navigating by screen-reader — designing for someone who isn't you starts by becoming them.
Available · 4 weeks' notice · GMT+5:30, US-East overlap
Selected Work
The AI work is the headline. The rest is the range under it.
Three AI products, one job in each: get a professional to trust the model enough to act on it. Two are LLMs reading unstructured documents. Details are confidential — I walk the real artifacts and numbers on a call under mutual NDA.
Programmatic Advertising Platform
Traders watched an algorithm beat them on the scoreboard and still played their own hunches. The fix wasn't a better model — it was a score tied to one action, reasons named out loud, and an override that taught next week's predictions.
Walk-through →AI-Assisted Private Equity Investing
Analysts get paid to doubt confident numbers, so I held the launch until the score could argue its own case. Once it could, they stopped auditing it and started leaning on it.
Walk-through →Technical Due Diligence Platform
Partners stake millions on technical claims they'll never personally verify. Extracting the signals was the model's job; getting partners to lean their reputation on the extraction was mine.
Walk-through →The rule behind every screen I ship
One score. One action.
An unexplained 87% is a shrug with decimals — it tells a person how the model feels, not what to do. So every confidence surface I design resolves to exactly one verb, with its reasons on the card.
How I Lead
Hire me and week one looks like this: I'm reading eval results before opening a design file, sitting silent on customer calls, and writing the diagnosis nobody assigned. By week two we're arguing productively.
The errata — a time I was wrong
I once fought hard for a recommendation card with three ranked options — give people choice, I argued. Engineering wanted one option, the top pick, nothing else. They won the meeting. Next quarter's A/B test made it permanent: the single-option card converted 2.3× better, because three choices froze people at the exact moment we needed them to move. Every recommendation surface I've designed since starts from that loss.
What you're hiring me to own
- The trust layer
- The exact pixels where a person decides the model deserves their click, or doesn't.
- The design language
- A component system the next designer can run without me in the room, because it's documented, not memorized.
- The ML/UX contract
- A written promise between the model team and the user: here's what this system can do, here's where it taps out.
How I work with engineering, product, and customers
- With engineering
- Eval design before interface design, always. The front-end I own ships in the PR — commented and ready for review. When we disagree on feasibility, the cheapest experiment goes first and settles it.
- With product / founder
- I'll contest the roadmap when the numbers contradict it, and I sign up for outcomes rather than deliverables. The design doc is mine to write; the spec is yours.
- With customers
- Five calls in my first week, one a week forever after, and I read the raw support tickets myself. No AI feature ships until I've personally watched someone fail to use it.
Three things I'll refuse
- Being the only designer in a company past 40 people — beyond that point design is an organizational problem, and one heroic hire is the wrong answer to it.
- Shipping an AI feature with no designed failure state — this one isn't negotiable, and if that's a dealbreaker we've saved each other an interview loop.
- Running design ops while also shipping product — it's two jobs, and doing both is how senior designers quietly do neither.
From the people who've shipped with me
Over the past four years at Talon, Arpit has been instrumental in shaping four distinct products from the ground up. His user-focused designs are remarkably intuitive yet adept at handling complex workflows… If you need a designer who excels at combining strategic vision with practical execution, Arpit is the person to call.
Arpit has worked with me for years and I value his honesty and hard work. He's been an integral part of my staff… involved in all facets of the team, from design to development to hiring and onboarding of new members.
Arpit teams up with designers very well, not only does he flawlessly execute the UI implementations but he pushes back on design decisions using his UX expertise… I'd recommend Arpit to any team looking to improve their final product.
Process
Every product is a series of bets someone else has to accept. The method exists to make each bet smaller, better-evidenced, and easier to say yes to.
Desirable · feasible · viable — the overlap is the bet worth making. Everything outside it dies in review.
Listen → Structure → Prove → Land, in loops — and every loop ends in front of a user.
Shipping is the first honest data. What users do returns as the next brief.
Writing
Three recent pieces from The Trust Layer, my newsletter on making AI products people actually act on.
More on The Trust Layer →The Agentic MVP: Why Your Next Launch Will Be Lovable, Not Just Viable
Every founder knows the pit in their stomach on Launch Day. How the rise of agentic systems is rewriting what "minimum viable" means — and why lovability is now the bar.
The AI Fight Club: Weaponizing Claude and Gemini for Bulletproof Products
Pitting AI systems against each other to strengthen product robustness. A practical method for stress-testing your AI features before users do it for you.
The New Renaissance: How AI is Transforming Us from Software Operators to Digital Artisans
Ushering in a new era of digital entrepreneurship. How AI is changing what it means to build, and what designers must understand about the tools reshaping the industry.
Contact
One seat. Full-time. Yours to offer.
I'm looking for exactly one role: founding designer at an AI product company of 5–40 people — or a staff / director seat where the trust layer is the actual job description. Fully remote from GMT+5:30 with 4–5 hours of daily US East overlap. Available — 4 weeks' notice.
Prefer to talk first? Book 30 minutes ↗I'll arrive having already used your product.
Prefer email? Loading…
The skim version: one page — positioning, receipts, references, availability →
Running a technical screen? It's already answered, in writing →
I reply within ~48 hours.
Not hiring but building something in AI? The patterns library and the founder checklist are free — take them.