In-depth articles on building scalable systems and backend engineering.
A practical walk-through of the streaming distribution problem, with exact design, chi-square uniformity, and the memory-bounded variant.
A practical guide to Python threading primitives, queue.Queue, asyncio.Queue, and when to use asyncio.to_thread.
A pragmatic playbook for handling bursty traffic with rate limiting, load shedding, backpressure, and retry control, plus a Dynamo-style case study.
A practical comparison of tiktoken and SentencePiece, including how BPE works, high-level pseudocode, and which model families use each.
Why Big-O can mislead in production and what to pay attention to instead: constants, cache behavior, input ranges, and p99 latency.
How to render OpenAI streaming responses smoothly in React and Next.js using requestAnimationFrame batching and UI-friendly buffering.
A grounded overview of jailbreaks, prompt injection, and layered defenses, with references to OWASP, OpenAI evals, and current research.
A practical breakdown of how Livegrep works, why indexed search feels instant, and how it compares to GitHub Code Search, Google Code Search, and grep.app.
A practical latency cheat sheet across caches, RTT, TCP/TLS handshakes, and LLM TTFT decomposition.
A practical OSI guide focused on debugging flow, fault isolation, and where latency hides in real systems.
A pragmatic guide to autocorrect, typeahead, and web-crawl dedup through the lens of latency, memory, and implementation tradeoffs.
A practical latency deep-dive: coast-to-coast RTT ranges, physics floors, handshake amplification, and how to budget for p95/p99 reality.
A practical bottom-up guide to modern LLM serving: KV cache, continuous batching, PagedAttention, speculative decoding, and disaggregated prefill/decode.
How to build resilient token streaming with SSE, Redis Streams, replayable offsets, and clean cancellation semantics.
Understanding how database indexes work and when to use them effectively.
Strategies for designing systems that gracefully handle failures and recover quickly.
Implementing effective rate limiting strategies to protect your APIs from abuse.