Warming up the neural circuits...
Eight levels. Seventy-five chapters. Seven projects. From "what is a TCP packet" to deploying an AI-powered backend with RAG — the path from beginner to senior engineer, in one course.
All 8 levels, all 7 projects, all 75 chapters. The complete path from L0 to L7. Lifetime access, no subscription.
Zero assumptions. How the internet, HTTP, DNS, databases, and auth actually work.
Node, Express, routing, middleware, CRUD, validation, error handling — done right.
Postgres, MongoDB, schema design, indexes, transactions, ORMs, migrations.
JWT, sessions, OAuth, RBAC, the OWASP top 4, secrets management, rate limiting.
Architecture patterns, WebSockets, queues, Redis, search, microservices, events.
Load balancing, replication, sharding, observability, case studies (Netflix, Uber, Stripe).
Linux, Docker, Compose, CI/CD, Nginx, SSL, cloud deploy, production debugging.
LLM APIs, embeddings, pgvector, streaming, RAG, agents — AI-aware backend in 2026.
Not blog posts. 3,000–6,000 words each, with real code, common-mistakes tables, and interview questions.
Each project is a complete, deployable backend — résumé-grade, not toy. From a CRUD API to RAG-powered SaaS.
Buy one level for a focused upgrade, or the full bundle at ~46% off. Each level is shippable on its own.
One-time purchase per level (or bundle). No subscription. Course content stays updated as the stack evolves.
Every chapter follows the same rhythm — why this matters, deep walkthrough, real-world example, common mistakes, exercises, interview questions.
How the Internet Works
DNS, IP, TCP, packets — explained from zero
Middleware Deep Dive
The single most powerful concept in Express
Indexes & Query Optimization
The biggest perf lever in your career
JWT Deep Dive
The token everyone uses and most people get wrong
Background Jobs & Queues
BullMQ, retries, DLQs — moving work out of the request cycle
Observability: Logs · Metrics · Traces
The three pillars + the one metric that predicts outages
CI/CD with GitHub Actions
Lint, test, build, deploy — every push runs the gauntlet
RAG: Retrieval-Augmented Generation
The pipeline that makes LLMs useful on your data
L0 is free. Start there. If it clicks, come back for the bundle.