How I Work
I think in systems. I design software to be reliable, scalable, and grounded in real user needs. Technical polish matters, but what matters more is creating tools that actually make someone’s work easier.
Leverage & Control
AI is a powerful force multiplier, but without rigid architectural oversight, it becomes a generator of technical debt.
My philosophy is to use AI to accelerate execution, not to replace understanding.
Architecture First, Generation Second
Code generation without a clear spec leads to endless "micro-refactoring" loops. I invest heavily in the planning phase, defining schemas, interfaces, and data flows before a single line of code is generated. This ensures AI outputs are integrated components, not isolated snippets.
Security & Boundaries
Maintaining strict data boundaries is non-negotiable. I utilize local LLMs for sensitive logic and sanitized contexts for cloud inference, ensuring that leveraging modern intelligence never compromises system security.
Core Methodology
The cyclical process I apply to every project.
1. Systems First
I design the system’s behavior up front, mentally walking through how data moves and how components should interact. With the flow already thought through, this lets me catch issues early and build with intention.
2. Research & Validate
I research existing tools and run quick experiments to understand the landscape. I prefer clean, focused custom code when it avoids bloat, but I’ll use a proven library when it’s clearly the faster, more reliable path.
3. Build & Iterate
I start with the core functionality, building a simple end-to-end flow first. Once the foundation works, I shape the UI around it so the experience feels natural and low-friction, then iterate and refine.
4. Feedback Loops
I rely on tight feedback loops, testing early and often to confirm the system behaves as intended. This helps reveal edge cases and ensures the final experience feels reliable and predictable.