to crack the AI interview loop
Become an AI engineer — master RAG, agents (LangGraph/MCP), evals & LLMOps and system design, through lessons, labs and voice mocks.
Everything interview prep is missing — in one place.
Three moves, repeated until it's automatic.
Learn by retrieving
Recall cards pull the answer out of your head. AI grades you and spaced repetition schedules the next hit.
Build it by hand
An in-browser Python IDE takes you from basics all the way to a deployment capstone.
Rehearse out loud
AI voice mock interviews put you on the spot and score your answers in real time.
How a question becomes an answer — every layer.
Foundations → Applied → Advanced.
In order.
Master the cards, clear the boss, move up. These are the real tier books from your dashboard — click a book to open it.
How LLMs work under the hood — text becomes tokens, tokens become vectors, vectors become predictions.
- ✓ Tokenization & vocabularies
- ✓ Embeddings & vector space
- ✓ Sampling & decoding
- …and more topics
FOUNDATIONS
Tier 1 · the vocabulary everything stands on
Turn the fundamentals into working systems — attention at scale, RAG, tool use, and how to evaluate what you build.
- ✓ Attention & KV-cache
- ✓ RAG pipelines
- ✓ Tooling & evals
- …and more topics
APPLIED
Tier 2 · applied LLM engineering
Ship it — quantization, efficient serving, deployment, and the systems-design thinking interviews probe hardest.
- ✓ Quantization
- ✓ Serving & inference
- ✓ Deploy & scale
- …and more topics
ADVANCED
Tier 3 · systems & deployment
FOUR TOOLS. ONE PLATFORM.
Learn it, build it, rehearse it, ship it — every surface you need to go from zero to interview-ready, without ever leaving the page.
Active-recall cards — Story or Focus mode, with an AI tutor.
You don't re-read — you retrieve, and an AI grades you. Flip any card between Story mode — an illustrated walkthrough — and Focus mode, a fast deep dive with diagrams, real Python and a tutor — then rehearse the real interview questions out loud.
A built-in Python IDE.
Read the problem, write the solution, run live tests — right here. Build the real things by hand, from a softmax to a LangChain RAG chain, with zero local setup. This is the app's actual Code screen.
Code arena
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Live voice mock interviews.
Speak your answers out loud to an AI interviewer — just like the real room. Get scored and corrected in real time, on quick daily drills or a full timed mock.
A real RAG system, end to end.
A 5-part capstone on a live LangChain kernel: build retrieval → add agents (LangGraph, MCP) → make it trustworthy with evals → ship it with FastAPI. A real project you can talk through in any interview.
Route hard queries to an agent
When retrieval isn't enough, hand off to a tool-using LangGraph agent — then merge the result back into a grounded, cited answer.
The questions that end interviews. You'll have answers.
Real gaps candidates freeze on. After 30 days, each of these is a walk.
“The retriever finds the right doc but the model still hallucinates. What do you check?”
Chunking, reranking, context order, and grounding — you'll have built each layer.
“RAG vs fine-tuning vs long-context — when do you reach for which?”
A decision you'll have made hands-on, not just read about.
“How do you evaluate a RAG system with no ground-truth labels?”
LLM-as-judge, RAGAS, faithfulness — drilled in the evals tier.
“Walk me through a tool-calling agent — and where it breaks.”
Tool-calling, LangGraph, MCP, and agent memory, built and rehearsed.
The interview layer video courses skip — without the bootcamp price.
An honest look. Bootcamps still win on live mentors and placement — that's what their price buys. On everything you can do yourself, tonight, Skillumen wins on speed, price, and the parts that make it stick.
The honest trade: bootcamps buy you a live mentor and a placement cell. Skillumen buys you the mocks, recall, and shipped capstone that get you interview-ready — flexible, transparent, for a fraction of the price.