Resources

Resources

Discipline rule: at most two sources per topic. A third source feeds the feeling of procrastination, not learning.

Month 1 — Database, HTTP, Docker

Book

• Designing Data-Intensive Applications — Martin Kleppmann. Chapters 1–3 are this month's backbone. (You'll return to Chapters 7–8 in Month 4.)

Database

• Official PostgreSQL documentation: the EXPLAIN, index types, and transaction isolation sections
• use-the-index-luke.com — one of the clearest sources on indexes

HTTP / REST

• MDN HTTP documentation (status codes, headers, caching)
• OpenAPI Specification — to understand what a contract is

Docker

• Docker's official "Get Started" + the Dockerfile best practices page

Month 2 — LLM and agents

• Your provider's official tool-calling documentation (primary source — look here before blog posts)
• Visual sources that explain the transformer conceptually (don't go into the math, stay at the "what/why/when" level)
• The pgvector repo's README

Month 3 — Eval

• Providers' eval/measurement documentation
• Read the design decisions of open-source eval tools (e.g., promptfoo, ragas) — not to copy code, but to see how they think

Month 4 — Scale

• Java Concurrency in Practice (relevant chapters)
• Python asyncio official documentation
• DDIA Chapter 7 (transactions) and 8 (problems of distributed systems)

Month 5 — Security and observability

• OWASP Top 10 + OWASP Top 10 for LLM Applications
• OpenTelemetry documentation (trace/span concepts)
• Prometheus metric types documentation

Month 6 — Storytelling

• Good README examples: analyze the READMEs of 3 open-source projects you like — which sections are there, in what order?
• Your own ADRs (raw material for the interview defense note)

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When adding a resource

Before adding a resource here: did you read/watch it? Adding a resource you haven't read turns the list into a dump.