AXLE · RAG & Context Engineering

RAG & Context Engineering

Building Production-Grade AI Systems. An eight-week, build-first program: you leave with a deployed retrieval-augmented AI system, the evaluation data to defend every design choice, and the judgment to know when each technique earns its place.

8 weeks · 1 live session/week
~6–8 hrs/week
Instructor: Pablo Grossi
100% hands-on · local-first tooling
View the full syllabus

How this program works

Every week follows the same professional rhythm: a live session where concepts are taught and the lab is built together, a checkpoint that becomes a permanent part of your capstone system, a weekend challenge that stress-tests what you built, plus curated reading and video. Nothing is throwaway — by Week 8 your weekly checkpoints assemble into one complete, deployed, evaluated RAG system running on a document collection you chose in Week 1.

From day one you work like a working engineer: local LLMs via Ollama, a real git repository, reproducible environments, and the rule that every claim gets tested with code — no copying framework defaults on faith.

The eight weeks

Week 1

When (and When Not) to Retrieve

What language models actually know, where they hallucinate, and the engineering decision that defines every RAG system.

Week 2

Classical Retrieval: BM25 and the Inverted Index

Fifty years of search engineering in one week — and the baseline every later technique must beat.

Week 3

Semantic Retrieval: Embeddings and Vector Search

Meaning as geometry: how embeddings find what keywords miss — and the chunking decision that quietly dominates quality.

Week 4

Hybrid Retrieval and Reranking

Neither keywords nor vectors win alone. Production systems fuse both — then let a heavier model re-order the shortlist.

Week 5

Evaluation: Diagnosing Failures Systematically

'It looks right' is not evaluation. This week you build the measurement machine that turns debugging from guesswork into diagnosis.

Week 6

End-to-End RAG and Multihop Retrieval

Wiring retrieval into generation properly — then handling the questions no single document can answer.

Week 7

Agentic RAG: Retrieval-Aware Workflows

From pipeline to agent: the model decides when to search, judges its own context, and re-queries until it can answer.

Week 8

Production: Secure, Observable, Deployable

The final mile: your system meets adversaries, latency budgets, and real users. Capstone week.

The capstone

Your final session is a defense, not a demo. You present your deployed system live, walk through the design decisions behind it — chunking, hybrid fusion, reranking depth, agent-vs-pipeline routing, injection defenses — and back every choice with your own evaluation numbers. You deliver it twice: once for a technical audience, once for stakeholders. That second version is often the harder one, and the more valuable skill.