Learning

A production-focused, visual explanation of the agent-native gateway pattern: how coding agents safely discover, authenticate, and call internal APIs, MCP servers, and third-party applications through an open-source enterprise stack.

A visual, source-grounded walkthrough of LLM inference and serving using nano-vllm and Mini-SGLang: tokens, prefill, decode, KV cache, scheduling, batching, prefix caching, CUDA graphs, tensor parallelism, and streaming.

A visual note on why advanced AI chips are shaped by packaging, memory, heat, alignment, power, cooling, and manufacturing.

A visual explainer about why AI chips are built around data movement, and how that turns into latency, batching, memory bandwidth, and long-context costs.

A small note on verbalized sampling and using AI to write more creatively.

Notes on how AI changes the way software gets made and learned.