As a CTO and technical leader, I focus on building scalable systems, empowering engineering teams, and solving complex technical challenges. My work spans full-stack development, AI integration, and microservices architecture, with a particular interest in how technology can enhance education and everyday experiences.
Throughout my career, I've learned that the best technical solutions come from understanding both the code and the people who write it. This perspective shapes my approach to leadership - balancing technical excellence with developer growth and well-being.
I believe deeply in the principles I wrote about in "AI Tools and Developer Growth" - that efficiency gains should translate to deeper learning, not just faster shipping. The best teams are those where developers are continuously growing their skills and understanding.
Perfect is the enemy of good, but good is the enemy of shipping. I advocate for finding the right balance: clean, maintainable code that solves real problems without over-engineering. Technical debt is fine if it's intentional and documented.
Good architecture isn't about using the latest technologies - it's about understanding trade-offs. Microservices aren't always better than monoliths. Distributed systems introduce complexity that must be justified. Every architectural decision should be made with clear reasoning and documented for future maintainers.
The role of a CTO isn't just to write code or make technical decisions - it's to create an environment where the entire team can do their best work. This means clear communication, good documentation, thoughtful code reviews, and building systems that are a joy to work with.
Frontend: Next.js, React, TypeScript, Flutter/Dart, modern CSS patterns
Backend: FastAPI, Flask, Node.js, RESTful APIs, microservices
Why it matters: End-to-end ownership allows me to make better architectural decisions and understand the full impact of technical choices.
Technologies: Google Gemini, RAG patterns, content generation, AI-powered workflows
Focus: Practical AI applications that solve real problems, not AI for AI's sake
Why it matters: AI is transforming how we build software. Understanding how to integrate it effectively - and when not to - is crucial for modern CTOs.
Patterns: API design, middleware layers, service orchestration, event-driven architecture
Experience: Building production middleware with authentication, connection pooling, and error handling
Why it matters: Scalable systems require thoughtful decomposition and clear service boundaries.
Technologies: PostgreSQL, Supabase, SQLAlchemy ORM
Specialization: Row Level Security (RLS), authorization patterns, data modeling
Why it matters: Data is often an application's most valuable asset. Proper security and design are non-negotiable.
Implementations: JWT, OAuth 2.0, dual-layer authentication, CSP headers
Approach: Defense in depth, principle of least privilege, security by design
Why it matters: Security can't be bolted on - it must be built in from the start.
Techniques: Connection pooling, async/await patterns, caching strategies, lazy loading
Philosophy: Measure before optimizing. Premature optimization is a trap, but ignoring performance is negligent.
Why it matters: Users judge applications by responsiveness. Performance is a feature.
Tools: Docker, Nginx, Raspberry Pi hosting, Let's Encrypt SSL
Approach: Infrastructure as code, automated deployments, monitoring
Why it matters: Understanding the full stack from code to infrastructure enables better architectural decisions and faster debugging.
I'm exploring the evolving role of CTOs in AI-first companies, where the challenge isn't just building software, but building systems that learn and adapt. This requires new patterns for testing, monitoring, and managing AI-powered features. Within this broader context.
I'm particularly drawn to the intersection of AI and education - how we can use technology to create personalized learning experiences at scale. My recent work with EduVideoAI reflects this focus, exploring how AI can transform existing content into targeted educational materials.
Beyond building and shipping products, I'm starting to share what I've learned through writing. I'm working on a series about technical leadership that explores architecture decisions, team building, and the balance between velocity and sustainability - the lessons that come from years of making mistakes, learning from them, and occasionally getting things right.
I work with CTOs, VPs of Engineering, and senior technical leaders who are navigating the transition from individual contributor to strategic leader, scaling teams, or facing complex architectural decisions. The shift from writing code to enabling others to write great code requires a different skillset - one that balances technical depth with people leadership.
My coaching is designed for technical leaders who are:
Effective coaching isn't about providing answers - it's about asking the right questions and creating space for leaders to develop their own solutions. I bring technical credibility combined with leadership experience, which means we can dive deep into architectural trade-offs one session and discuss team dynamics the next.
Sessions are practical and action-oriented. We focus on real challenges you're facing right now, whether that's a specific technical decision, a team conflict, or strategic planning. I provide frameworks and perspectives drawn from my experience, but ultimately, you're building your own leadership philosophy.
Technical Strategy: Making architectural decisions that balance current needs with future scalability. Understanding when to refactor, when to rebuild, and when to live with technical debt.
Team Building: Hiring, developing, and retaining engineering talent. Creating career paths, conducting effective 1-on-1s, and building a culture of continuous learning.
Communication: Translating technical concepts for non-technical stakeholders. Making the case for infrastructure investments, managing up effectively, and influencing without authority.
Process & Delivery: Establishing engineering processes that enable velocity without chaos. Balancing speed with quality, planning with flexibility.
AI Integration: Navigating the rapid evolution of AI tooling. Building AI-powered products, managing AI-assisted development, and understanding where AI adds value versus where it creates risk.
If you're a technical leader looking for a thinking partner who understands both code and people, I'd welcome a conversation about how coaching might support your growth.
I share my thoughts through writing on Medium and Substack, focusing on technical depth over hot takes. My articles explore topics like AI and developer growth, system architecture, and technical leadership.
All my projects are open source (or will be soon), because I believe in learning by sharing. You can find my work on GitHub.
I'm always interested in conversations about technical leadership, system architecture, AI integration, or building great engineering teams. Feel free to reach out through LinkedIn, GitHub, Medium, or Substack.