Curriculum
24 weeks. 6 phases. The order is the curriculum.
Below is the public outline. Lesson-level content unlocks after you sign in. The structure is identical for every cohort — that consistency is the point.
03 / The 24 weeks
Six phases. In this order. No reordering, no skipping.
The structure is the result of looking at how OpenAI, Anthropic, Palantir, and Salesforce actually onboard and deploy engineers. The two phases other programs cut are the two we defend hardest.
- 01Weeks 1 – 4
Production Codebases
Reading code you didn't write. Distributed systems vocabulary credible enough for Phase 2.
Capstone→ Time-to-first-patch in an unfamiliar OSS project - 02Weeks 5 – 8
LLM Engineering Core
RAG, agents, tool use, prompt engineering. Build the systems you'll later rip apart with evals.
Capstone→ Domain-specific RAG with hybrid retrieval - 03Weeks 9 – 12
Eval-Driven Development
Defend this phaseError analysis, LLM judges, eval CI. Measure first, build second. The phase that compounds.
The differentiator. Most courses skip this. Engineers who finish this phase well are ahead of 80% of the candidate pool.
Capstone→ Evals-first refactor of the Phase 2 RAG project - 04Weeks 13 – 16
Production System Design
Multi-tenant AI architecture, cost & latency budgets, failure modes you only see at scale.
Capstone→ 15 – 20 page architecture proposal for a real client scenario - 05Weeks 17 – 20
Client-Facing Skills
Defend this phaseDiscovery, scoping, stakeholder management, pushback. The skills that decide whether a deployment ships.
What most programs skip and what makes deployments fail. Code that works doesn't ship if no one trusts the engineer holding it.
Capstone→ Internal discovery → proposal → prototype → present - 06Weeks 21 – 24
Engagement Simulation
Synthesize everything under realistic client pressure. A simulated 4-week engagement, graded on a 5-axis rubric.
Capstone→ Full simulated engagement, manager review, written retro