// Topics
Topic hubs
Curated entry points into the deepest threads on this site. Each hub gathers the posts on one subject into a reading path, from fundamentals to production detail.
AI Agent Architecture
The patterns, trade-offs, and failure modes behind production AI agents. From the agent loop and tool calls to multi-agent design and error handling.
AI Agent Memory
How production AI agents store, retrieve, and forget information. A practitioner's guide to memory architecture, from context windows to episodic recall, backed by benchmarks.
AI Workflows & Automation
How to wire AI agents and coding assistants into real work: choosing models, setting up coding agents, connecting tools with MCP, and automating the busywork without losing control.
LLM Inference & Cost
How LLMs actually run, and how to make them faster and cheaper. Context windows, token budgets, prompt caching, speculative decoding, TTFT, and KV-cache internals, all benchmarked.
RAG & Retrieval
A practitioner's guide to retrieval-augmented generation: embeddings, hybrid search, reranking, evaluation, and the optimizations that decide whether your RAG system works.
Technical Writing for DevTools
How to write documentation, tutorials, and developer content that engineers respect and buyers act on. The craft, the business case, and what separates practitioner writing from marketing.