Engineering
Real engineering stories from production. No client names, no corporate framing — just the interesting problems, the approaches that worked, and the lessons I took away.
Approach
Instead of a costly rewrite, we profiled the bottlenecks, fixed the database schemas, and introduced targeted job queues for heavy background tasks.
What I learned
"Most scaling problems don't need microservices—they need better indexing, smarter queues, and simple caching. Keep it boring, keep it fast."
Approach
Built structured evaluation pipelines, implemented strict fallback chains, and added observability to track every token and decision the LLM made.
What I learned
"LLMs are incredibly flaky infrastructure. You have to wrap them in traditional software engineering practices—timeouts, retries, and circuit breakers—to make them reliable."
Approach
Restructured the React Native architecture, moved heavy blockchain operations off the main thread, and implemented an efficient WebSocket layer.
What I learned
"Mobile performance is almost entirely about state management and thread blocking. Get your data model right early, and the UI will stay smooth."
Approach
Audited the AWS bill, right-sized over-provisioned instances, implemented auto-scaling, and heavily utilized CDN caching to reduce origin hits.
What I learned
"Cost optimization is an engineering problem, not an accounting one. Small architectural tweaks like moving caching to the edge can slash bills by 40% overnight."