Lara Mateo Portfolio
Tech Lead & AI Product Engineer; Founder, Kenda
A "case studies" section instead of a project list — each entry names the problem, the constraints, and the outcome, backed by a live AI FinOps startup and two open-source MCP servers with real GitHub stars and contributors.
Location
Buenos Aires, Argentina
Companies
Skills
Notable
- Founded Kenda, an AI FinOps platform live at kenda.app with SOC 2 Type II in progress
- Marksight (open-source Markdown-to-Claude-Skill editor): 18 GitHub stars, 11 contributors, 100+ users
- Umbryn MCP: open-source PHI/PII redaction server published to PyPI
- Invited closing speaker, Café Cursor #4 (Buenos Aires, August 2026) on building MCP servers
- Went from Senior Engineer to Tech Lead in ~6 months at Clarity RCM, a HIPAA-regulated healthcare platform, leading a team of up to six
What makes it work
A breakdown of the choices that make this portfolio stand out.
Case studies framed as problem → constraints → what I did → outcome
Instead of a screenshot-and-tech-stack project grid, the two featured case studies (the Tech Lead promotion, the Core Web Vitals work at ReflexAI/Mercado Libre/GlobalLogic) are written as structured narratives with an explicit "what I took from it" reflection. That last section is unusual — most portfolios stop at the outcome and skip the self-assessment.
Side projects that form a visible thesis, not a grab-bag
Umbryn redacts PHI/PII before it reaches an LLM, Marksight turns documents into Claude Agent Skills, Kenda reconciles what AI agents actually cost — three different projects that all attack the same problem (the unglamorous infrastructure agentic AI needs before it is trustworthy in production). The GitHub README states this pattern explicitly rather than leaving it for the visitor to notice.
Verifiable open-source footprint, not just claimed skills
The Umbryn and pls-touch-grass MCP servers link to live PyPI/npm packages and GitHub repos with actual commit history; Marksight shows 18 stars and 11 contributors on GitHub. The GitHub profile independently corroborates the site's claims (same founder title at Kenda, same pinned repos, cross-links back to laramateo.com) rather than the portfolio being the only place the claims exist.
A talk that admits the demo broke
The "Building MCPs in Cursor" talk writeup and the linked blog post don't sand off the failure — the agent got frustrated mid-demo, started editing the presenter's code, and broke the MCP live on stage. Leading with that instead of a polished highlight reel is a distinctive, checkable (YouTube link, GitHub demo repo) piece of content most portfolios wouldn't include.
What AI Engineers can take from this
Specific, actionable tips to apply to your own portfolio — no generic advice.
Write project write-ups as problem → constraints → what you did → outcome, and add a closing "what I took from it" line — it reads as reflection, not a résumé bullet restated.
If your side projects share a theme, say so explicitly in one sentence. A reader forgives three portfolio projects; three projects that are visibly one thesis reads as intentional expertise.
Link every claimed tool or package to its live PyPI/npm/GitHub page. A named MCP server with no working link is a claim; with one, it is a fact anyone can check in ten seconds.
Cross-link your portfolio and GitHub profile to each other, and keep the bio consistent (same title, same current company) on both. That consistency is what makes a corroborating link actually corroborate.
A demo that goes wrong is more memorable and more credible than one that goes perfectly — if you have one, write it up instead of hiding it.
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