Deep technical breakdowns from projects where milliseconds, reliability, and maintainability matter. Compilers, AI infrastructure, and performance engineering.
How we reduced LLM failure rates by 65% through structured outputs, validation, and systematic testing.
“Building production guardrails that keep language model features predictable and debuggable.”
Lessons learned from deploying RAG systems for EdTech: multi-tenancy, security, and achieving >90% retrieval accuracy.
“Designing a resilient retrieval-augmented generation platform for multi-tenant education workloads.”
Deep dive into vectorization cost models and architecture-specific optimizations that achieved 3x performance improvements on NASA benchmarks.
“Tuning LLVM vectorization and instruction selection to unlock 3× performance on real-world scientific workloads.”
Technical insights from implementing AST bridging and name mangling compatibility in the Swift/Clang toolchain at Apple.
“Extending the Swift compiler to seamlessly call modern C++ libraries without sacrificing safety or performance.”
I partner with teams shipping compilers, AI platforms, and performance-critical systems. Let’s turn the insights into production wins.
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