hub.gazar.dev · course

Production-Ready Systems with LLMs and Agents

Build LLM and agent systems that survive real traffic, cost, and failure. The part the framework tutorials skip: the architecture decisions that make LLM and agent systems hold in production. Twelve 90-minute live sessions and five production-grade artifacts, over six weeks, and every week ships with a slide deck, a cheat sheet, and a hands-on coding lab. maven.com/gazar/production-ready-systems-with-llms-and-agents · Companion code (TypeScript + OpenAI): github.com/ehsangazar/maven-llms-and-agents-6-weeks

Every lab ships as runnable code

TypeScript and OpenAI, behind one provider seam you can swap. Clone the companion repo, or jump to a lab's code under its week below.

github.com/ehsangazar/maven-llms-and-agents-6-weeks ↗

A field guide to the tools

Each week below ends with the common tools for that stage of the stack. Every tool has a decision-first page: what it is, the one job it does, when to reach for it, when to skip it, and where it fits your labs. The tools are a means; the architecture is the lesson.

Pre-course · set the target

Before Jul 13

Week 1 · Foundations: workflows, agents & the code/model boundary

Jul 13 – 19

Week 2 · Context engineering & retrieval

Jul 20 – 26

Field guide · tools for this week

Week 3 · Cost, latency & reliability

Jul 27 – Aug 2

Field guide · tools for this week

Week 4 · Agent architecture & security

Aug 3 – 9

Week 5 · Evals & observability

Aug 10 – 16

Companion code

Week 6 · Capstone: design, present, defend

Aug 17 – 23

Field guide · pull it together

Small-group intensive. Each Tuesday teaches the concept and its trade-offs; each Thursday is a workshop where you apply it to your own system and build that week's slice of a production-grade artifact. Taught by Ehsan Gazar, Principal Engineer, 16 years in production systems, 500+ mentees.