Let’s build something that ships.
I ship agentic AI that engineering teams actually adopt. Not demos. Not pilots that quietly die. Things that stay shipped.
psst — try the ? key
I turn fuzzy ideas into tools people actually use. Not demos. Not decks. Things that ship and stay shipped.
My background is a weird mix — engineering, design, innovation labs, teaching, and a bookshop startup. Turns out that combination is exactly what you need to build AI that works for real humans in real orgs, not just in notebooks.
Ship, then polish
The best tool is the one people are already using. I'd rather put something real in front of someone tomorrow than something perfect in front of nobody next quarter.
AI is a means, not a flex
I don't build AI because it's cool. I build it because some tasks are too boring, too slow, or too error-prone for humans to keep doing by hand.
Understand the room
Design background, innovation labs, teaching. I've learned to talk to stakeholders, not just compilers — which is usually where "AI projects" quietly die.
Spanish · English
Universidad de Montevideo · Coderhouse
DeepLearning.AI · Cambridge C2
Reading the skill card out loud
The terminal up top showed the spec. Here’s what it means in practice — when to invoke me, and what you get back.
- invoke
- : martin-brian
- handles
- : fuzzy idea → production
- returns
- : a thing that ships
- whenA team has an AI idea and no clear path from prototype to production
- whenSomething agentic needs to survive real infra — latency, reliability, cost
- whenStakeholders need explaining as much as the code needs writing
May cause people to stop asking “does AI actually help?” and start asking “how did we work without this?”
The story so far
Marvik → dLocal
Making AI do the boring parts
Embedded in dLocal's AI team, where I ship agentic systems on a Claude Agent SDK / Claude Code base. The one that rolled out across the engineering org drives 40%+ end-to-end automation of dev tasks on a high-availability fintech platform. People stopped asking "does this help?" and started asking "how did we work without it?"
Ulta Beauty · Innovation
AR, AI, and a Fortune 500
Contributed to GLAMlab — Ulta's AR/AI virtual try-on and its first public generative AI app. Built a video analysis engine that watches affiliate and influencer content for brand-guideline violations at scale. Plus supporting iOS, web, and backend work across innovation projects.
BroLi · Co-founder
Running a bookshop with code
Co-founded and led engineering at an independent bookshop that applied blockchain and AI to a category that usually ignores both. Owned the stack end to end, led a small team, learned that startups are 20% code and 80% everything else.
Universidad de Montevideo · Octobot
Teaching, shipping, learning
Taught innovation and life-design workshops at UM's corporate innovation lab. Before that, shipped Django/React web and Swift/SwiftUI iOS at Octobot. The teaching part stuck — I still think of great engineering as mostly good explanation.
Things I've built
The projects that taught me the most — or that I just can't stop talking about.
40% Dev Automation
The system that changed how an entire engineering org works. Model-agnostic agents that handle code reviews, test generation, and routine development — all running in production on fintech rails.
GLAMlab
Ulta Beauty's AR/AI virtual try-on. Millions of users on iOS and Android, and the company's first publicly-recognized generative AI application.
Brand Compliance Engine
Watches thousands of influencer videos and flags the ones that break the rules — mentions of competing brands, quality issues, policy violations. Built to replace a team of humans squinting at screens.
Let’s connect
Open to conversations about AI engineering, agentic systems, and interesting problems worth solving.
hello@martinbrian.com