Python, async and FastAPI — build your first working API
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Live cohort25 seatsMon–Fri
A live engineering cohort where you build retrieval, agents and evaluation the way production requires — and an engineer reads every line you write.
Cohort capped at 25Python taught from scratch
Month 3, week 2. Retrieval quality, reranking, evaluation and token cost — the parts tutorials skip.
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Live classesMon–Fri, taught live. Not a video library.0
Projects shippedReviewed line by line on your own repo.0max
Seats per cohortCapped so the review is real.0
Months3 learning, then 1 building and shipping.01 — The honest comparison
You don't pay for the information. You pay for the things a tutorial has no incentive to teach you — and for someone who reads your code.
Typical course: A notebook demo on someone else's clean PDF
Here: You ship a deployed AI product with real users in mind
Typical course: One retriever, no measurement of whether it works
Here: Retrieval quality, reranking and evaluation are taught
Typical course: Cost ignored until the API bill arrives
Here: Token cost, caching and rate limits are part of the build
Typical course: Security not mentioned at all
Here: Prompt injection and unsafe tool execution are handled
Typical course: No one ever reads your code
Here: Live mentor review on your actual repository
The difference is not content. It is consequence. A tutorial ends when the demo runs. Production begins there.
02 — Programs
One path. One outcome. One cohort at a time. Choose by the role you want, not the technology you already know.
03 — Review
Engineers who build — not influencers who record. Here is the mechanism, so you can judge it before you pay for it.
Not a sandbox, not a course platform. Your GitHub, your commit history, the thing a hiring manager will open.
Pull-request style feedback on structure, tradeoffs and readability — weekly, on the code you actually wrote.
In office hours you explain your decisions out loud. This is the rehearsal for every technical interview you sit.
04 — Curriculum
Three months learning, one month building. No prior Python, no maths background, no machine-learning theory.
Python, async and FastAPI — build your first working API
PostgreSQL, auth, Docker, deployment + your first LLM integrations
Prompt engineering, embeddings, vector DBs, RAG and AI agents
Build month — ship, harden and deploy your own AI products
05 — Fit
Read the right-hand column first. If you are in it, close the tab — we would rather lose the sale than take the money.
Ask questions, share what you are building, and hear first when a new cohort or free lesson goes live.
Free · Leave anytime
06 — Before you apply
No. Python is taught from scratch inside the program, in the depth an AI Engineer actually uses it. You need no machine learning, maths or research background — month 1 starts at setup and variables.
Live classes are Mon–Fri, 1–1.5 hours a day. With practice, plan for 7–10 hours a week. It is designed to fit around a job or college.
76 live classes across 4 months, 12 hands-on projects, weekly 1:1 code review, direct mentor access for doubts, lifetime access to material and recordings, and a cohort capped at 25 so your work actually gets reviewed.
Free tutorials show a working demo on clean sample data. This program takes you to a deployed system — retrieval quality and reranking, evaluation, token cost control, rate limiting and prompt-injection defence — with someone reviewing your actual code.
Every class is live, Mon–Fri, with recordings afterwards. Nothing here is a pre-recorded-only video library.
A new cohort starts every month, so there is always one to join. Reviewing the curriculum costs nothing — it is published in full before you pay.
New cohort monthly · 25 seats · Live Mon–Fri