Production-Ready Systems with LLMs and Agents
Your demo works. Production is a different system. Workflows versus agents, context that decays, cost and latency budgets, agent threat modelling, and evals that catch a silent regression before your users do.
$1,500 live cohort$299 self-paced, same curriculum
Full refund if the first module doesn't change how you design.
About This Course
Most production-AI material still teaches the 2025 threat model: prompt injection and output quality. The problems senior engineers actually hit in 2026 moved. The agent stack became opaque, providers change behaviour inside a pinned version without announcing it, the tooling you install has repo and credential access and auto-updates, and integration convenience is billed in context on every single request.
The through-line of this course is control and observability over systems you do not own. Eight modules and sixty-one lessons: thirty teaching lessons, six cheat sheets, six labs, seven projects you run against your own system, field guides to thirty tools so you can choose rather than adopt, and a capstone of six production LLM systems designed end to end.
Every lab is specified end to end, with the steps, the acceptance criteria and the code shape; the companion TypeScript repo ships a full starter, solution and test suite for the first lab, and you build the rest in your own codebase.
Start Here is free to read, and so is one of the six worked designs from the capstone.
Course Curriculum
8 modules · free lessons open to everyone
$1,500 live cohort · same curriculum, self-paced
Full refund if the first module doesn't change how you design.
What You'll Learn
- Start Here
- Workflows and Agents
- Context Engineering and Retrieval
- Cost, Latency and Reliability
- Agent Architecture and Security
- Evals and Observability
- Shipping It
- Capstone: Worked LLM System Designs
Ready to level up?
61 lessons across 8 modules. Start with the free module, then unlock the rest.