Find the right evidence.
Turn documents into searchable knowledge. Compare lexical and semantic retrieval, then build and evaluate a hybrid pipeline.
VIBEGRAPH × THE CONTEXT LAYER
THE CONTEXT ENGINEERING LAB
Build the context.
Trust the output.
Go from scattered knowledge to grounded AI. Learn retrieval, context design, and evaluation by building a system you can actually inspect.
8 modulesSelf-pacedPython + practical labs
CONTEXT ASSEMBLY 001 / CONTEXT MAP
context knowledge
constraints
memory
evidence
LESS NOISE. MORE SIGNAL.
24Written lessons
16Hands-on labs
48Knowledge checks
01Portfolio capstone
01 / A DIFFERENT KIND OF AI COURSE
The model is only
part of the system.
You decide what the model sees, what it can do, and how to tell whether it worked. This course gives those decisions structure.
Make failure visible.
Separate retrieval failures from answer failures. Build an evaluation set and use evidence to choose your next improvement.
Design for real use.
Work through permissions, prompt injection, latency, cost, and release decisions. Explain the trade-offs behind your system.
02 / THINK IN EVIDENCE
Watch a question
find its context.
Explore three small fictional examples of evidence-led answers. The full lessons, exercises, and datasets are in the paid classroom. No live AI call is involved.
RETRIEVAL INSPECTORWORKED EXAMPLE
01
When is the studio open?
02
03
Relevant text is a starting point. Claim support still needs evaluation.
03 / THE CURRICULUM
Eight modules.
One connected build.
Follow an eight-week rhythm or move at your own pace. Each module combines explanation, a worked example, two labs, and a six-question check.
Loading curriculum…
START WHERE YOU ARE
Basic Python, JSON, and API familiarity recommended. Plan roughly 40–60 hours for reading, practice, and a thoughtful capstone. Time varies with experience and project scope.
04 / WHAT YOU WILL BUILD
Your knowledge.
Your context layer.
Finish with a grounded assistant and the evidence to explain how well it works.
Choose an internal knowledge assistant or a customer-support assistant. Bring an authorized dataset, or start with the included fictional corpus.
Explore the capstone01
A versioned knowledge pipeline
02
A context and permissions contract
03
A reproducible evaluation report
04
A release decision and rollback plan
A working reference project, developed and assessed by you. No university credit or accredited certification.
05 / PRACTICAL SKILLS. ACCESSIBLE PRICE.
Invest in the skill.
Keep it accessible.
An original, self-paced course for people who learn by building.
Written lessons. Runnable examples. Transparent trade-offs. Everything is organized around work you can inspect and improve.
The price is 1/100 of the $5,376 promotional tuition observed for the MIT xPRO reference program on October 19, 2026. The formats, support, and credentials differ. View the comparison →
THE COMPLETE LAB
$53.76
USD · one-time course enrollment
- 8 modules and 24 written lessons
- 16 practical labs with solution guidance
- 48 quiz questions with explanations
- Python lab kit and synthetic datasets
- Capstone brief and assessment rubric
- Progress, notes, and offline handbook
Secure Stripe checkout. Sign in with ChatGPT for course access. Optional model APIs and compute are separate.
Preview the course format →06 / BEFORE YOU START
A few things
to know.
Who is this course for?
Developers, technical product builders, GTM engineers, and AI practitioners who can read basic Python and want to build grounded AI workflows. If APIs and JSON are new, start with the orientation and allow extra practice time.
Is this an MIT course?
No. This is an independently created course by vibegraph and The Context Layer. The public MIT xPRO topic outline was a scope reference. The lessons, examples, labs, and assessments here are original. It includes no MIT instruction, certificate, endorsement, or affiliation.
What do I need to run the labs?
Python 3.10 or later and a text editor. The core retrieval labs use only the Python standard library. Optional learned embeddings require a model download and an additional package. Real LLM generation requires your own provider account and API budget.
Are there videos, live sessions, or a tutor?
This edition is a written, self-paced course. It includes worked examples, solution notes, quizzes, and a capstone rubric. It does not include recorded lectures, live teaching, human grading, or an AI tutor.
Where is my progress saved?
Lesson completion, quiz scores, and notes stay in this browser. You can export a progress backup and import it on another device. Browser storage can be cleared, so keep a backup. There is no account sync in this edition.
Can I purchase it now?
Open enrollment to see availability. Sign in with ChatGPT, review the delivery terms, then pay through Stripe. A confirmed payment unlocks the full course and downloads for that account.