Case study
Marketplace for Design Talent
Designtalent.AI is a curated marketplace for contract design work, built on trust. I founded it and designed, coded, and shipped the two-sided product solo, working with an AI copilot, from 0 to 1, defining its information architecture and flows.
Launched October, 2026.
Business Outcomes
About
Built on trust, for both sides.
Companies find vetted specialists for critical work. Designers find meaningful work with clients who value craft.
Talent pays $0 in fees and keeps 100% of their rate. Companies pay a simple 12% platform fee. Referral bounties are set and funded by the hiring company.
The problem
Hiring design talent for critical work was slow, uncertain, and built on guesswork.
Business and people problem
Hiring design talent for critical work is slow and uncertain. Companies can’t easily tell who’s actually good, hiring managers were guessing from portfolios, and great designers had no trusted channel to contract work without giving up a share of their rate to an agency or platform, losing part of every paycheck to middlemen. Neither side had a reason to trust the other before the work started.
Opportunity
Introduce a curated marketplace where every designer is personally reviewed and approved before they join, and matching is transparent, with skill-based match scores, messaging, identity verification, and payments built in.
Constraints
A solo build, trust earned from zero, and a two-sided cold start.
- Solo build, one person designing and shipping everything.
- Trust had to be earned from zero: no brand, no track record, no employer network at launch.
- Two-sided cold start, talent without companies, and companies without talent, so the talent pipeline came first.
- No open signups: every designer is personally reviewed, which is a deliberate constraint on growth.
- Real money and identity from day one: payments and verification had to be right at launch.
My role
Founder, designer, and builder, responsible for the whole product.
Product strategy and positioning, including the trust-first model and the fee structure.
Designed the end-to-end experience for both sides of the marketplace, talent and company.
Designed the trust and vetting system: application review, identity verification, and the verified badge.
Designed skill-based matching, including top skills, must-have and nice-to-have skills, and employer match scores.
Designed messaging, applications, and the hiring flow.
Designed payments, including Stripe integration, the 12% platform fee, and referral bounties paid at 80 hours.
Designed the public directory, featured profiles, Dream Teams, and referrals that grow the bench.
Shipped in daily bundles, tested live with real users, and iterated from what they reported.
Owned brand and launch assets, including the public launch and the LinkedIn company page.
How I led it
As the only product designer, I had to align three sides at once: the talent, the companies, and the recruiters.
The hardest call was which AI tool to build with end-to-end. I started with Lovable and Bolt to compare the platforms, and ended up choosing Muse as the AI coding assistant.
The tradeoff was balance. I had to design and build the platform while simultaneously developing the talent pipeline and onboarding companies and recruiters, growing the product and the marketplace at the same time.
The work
Both sides of the marketplace, designed end to end.
Outcome
Live since October, 2026 with 50k LinkedIn post impressions on launch day.
The live marketplace brings it all together: a public directory, featured profiles, referrals, Dream Teams, the verified badge, and payments through Stripe, tested live with real users from launch.
Next project
Microsoft, Designing for AI
Owned UX end-to-end for an AI-powered digital assistant for Brazil’s largest bank (98M+ customers), shipping the MVP in 4 months.