Context Engineering

System design fundamentals for AI engineers: client-server, APIs, latency percentiles, caching, load balancing, databases, and queues — each explained from zero, then mapped to how LLM systems change it.

The 60-term plain-English glossary for AI system design: LLM basics, retrieval, agents, infrastructure, reliability, scaling, cost, and safety — with deep-dive links into every guide section.

Build a support bot end to end: six iterations from one API call to a production-shaped architecture with retrieval, caching, model routing, guardrails, and observability — runnable code at every step.

Traditional vs agentic system design: the 7 dimensions that transform, anatomy of an agentic system, control flow paradigms, failure modes, and when to go agentic.