Building practical AI products, multilingual web systems, and technical infrastructure for teams that want to ship with clarity.
I work at the intersection of AI engineering, product architecture, and full-stack software. My focus is turning new AI capabilities into usable systems: reliable interfaces, clear workflows, responsible automation, and infrastructure that can actually run in production.
Current areas of focus:
- AI-native products that combine LLMs, agents, retrieval, structured workflows, and human review
- Full-stack applications with React, Next.js, TypeScript, Python, and API-first backend design
- Bilingual and localized software for English and Spanish-speaking audiences
- Responsible AI implementation with practical controls around accuracy, safety, and transparency
- Founder-led product work through TriHerm
Languages TypeScript, Python, JavaScript
Frontend React, Next.js, Vite, Tailwind CSS, shadcn/ui, Radix UI
Backend FastAPI, Express, serverless APIs, REST integrations
Data PostgreSQL, Supabase, JSON, RSS/XML parsing, data pipelines
AI OpenAI, Gemini, LLM workflows, agents, inference optimization
Infra Docker, Vercel, self-hosted services, GitHub Actions
Quality TypeScript strict mode, ESLint, Vitest, pragmatic testing- Ship useful systems: AI should reduce friction, not add another confusing layer.
- Design for production: latency, cost, observability, permissions, and failure modes matter early.
- Keep the interface honest: the user should know what the system can do, what it cannot do, and when a human needs to decide.
- Build for more than one audience: localization, accessibility, and clear language are product requirements, not polish.
I write about AI, product, and technology on blog.triherm.com.
Recent topic:
- El rol de la IA en el desarrollo de software del futuro — how AI is becoming part of everyday software engineering, and why the strongest teams combine human judgment with model-driven acceleration.
I am interested in work around:
- AI product development for startups, SMBs, and technical teams
- LLM-powered internal tools, assistants, and workflow automation
- Multilingual SaaS and web platforms
- Responsible AI strategy and implementation
- Technical writing, research, and open-source developer tools