Follow a subject.
Every topic pulls together everything about it — the handbook, the system design, the algorithm game, the runnable challenge and the tool — so you can go deep on one subject instead of hopping between 11 separate catalogs.
AI Engineering
RAG & Retrieval
Retrieval-augmented generation end to end — chunking, embeddings, similarity search and ranking — across a system design, a hands-on tool, and runnable challenges.
LLM Engineering
Building with large language models — prompting, decoding, inference serving and cost — from the handbooks down to the softmax that powers every token.
AI Agents & Tools
Agentic systems — tool calling, orchestration and the interfaces that let models act — with the agent system design, the agentic interview handbook, and a tool-schema designer.
AI Evaluation
How you know an AI system actually works — LLM-as-judge, agent evals, and metrics like token-F1 — the half of AI engineering that separates demos from production.
ML Foundations
The math under the models — gradient descent, softmax, embeddings, similarity and ranking — taught as playable labs and runnable challenges.
Systems & Backend
Distributed Systems
Consistency, consensus, replication and coordination — the CAP-theorem-shaped trade-offs at the heart of every large-scale system, with handbooks, system designs and interactive tools.
Databases & Storage
Storing data at scale — transactions, isolation, indexing, ledgers and sync — from the concurrency handbook to systems like Dropbox, a payment ledger and a key-value store.
Caching & Performance
Making systems fast — caching strategies, CDNs, rate limiting and low-latency design — with a capacity estimator and the systems that live or die on cache hit rates.
Real-time & Messaging
Pushing data the moment it changes — WebSockets, fan-out, streaming and message queues — across chat, feeds, notifications and collaborative editing.
Foundations
Algorithms & DSA
Data structures and algorithms taught as playable games and runnable challenges — graphs, sorting, search and dynamic programming, the half of every interview loop you can practice.
Interview Prep
Everything pointed at the interview loop — AI and system-design handbooks, language Q&A, the DSA roadmap and runnable coding challenges in one place.