Engineering Philosophy
Six principles that guide how I build systems, write code, and approach technical challenges
Architecture Over Shortcuts
Good system design outlives quick hacks. I prioritize scalable, maintainable architecture over fast fixes that create technical debt.
Production-Ready AI Systems
AI demos are easy. Production systems are hard. I focus on reliability, monitoring, error handling, and cost optimization—not just cool features.
Backend Reliability First
Users don't see backend code, but they feel it. Every millisecond matters. I obsess over latency, caching, database optimization, and failure recovery.
Performance-First Thinking
Fast systems enable better user experiences. I profile, benchmark, and optimize ruthlessly—from database queries to API response times.
Practical GenAI Integration
LLMs are tools, not magic. I evaluate where they add real value vs hype. RAG, prompt engineering, and cost control matter more than model size.
System-Level Design
Great code is just one part. I think in systems—databases, caching, message queues, observability, deployment pipelines, and how they all connect.
Let's Build With These Principles
If these resonate with you, let's collaborate on production-ready AI systems
Get In Touch