Free resources for developers

A free overview of how to plan a preparation timeline, what to study in what order and how the rounds fit together. Read it before deciding what to buy or who to book.

An automated review of your resume against what technical recruiters screen for, returning specific changes rather than a score. Useful as a first pass before you ask a human to look at it.

A free, browsable index of system design concepts and worked questions, useful as a reference while you practise. A good way to judge whether the paid material is for you before paying for it.

Design prompts to work through under time pressure, which is the part of preparation everyone skips. Reading designs builds recognition, producing them builds the skill being tested.

A browsable practice library organised by pattern and by data structure rather than by an arbitrary difficulty number, so you can drill exactly the weakness you found this week. Filterable by company as well.

The well known seventy five problem list, presented with the pattern each question belongs to instead of as a bare checklist. Free, and a reasonable place to test whether your preparation is actually working.

Per company breakdowns of the loop structure, the rounds you will face and what each one is scoring, for the major technology employers. Read the guide for your target company in the week before the loop, not the night before.

Recommendations, data pipelines, and a lot of writing about how engineering teams are organised and tooled. Read it for the developer experience posts as much as the architecture ones.

Messaging at scale, real time presence, search and the slow work of migrating a large PHP codebase without downtime. Practical, honest about constraints, and closer to the problems a normal company actually has.

Real time matching, geospatial indexing, payments and the long running story of moving off a monolith. The problems are concrete and easy to picture, which makes this a good blog to start with if architecture write ups usually lose you.

Posts on storage, caching, data centres and the infrastructure behind products used by billions of people. Uneven, and the good ones are very good, particularly anything about how a system was migrated while staying online.

The most consistently readable engineering blog in the industry. Deep posts on networking, DNS, TLS, caching and database scaling, plus unusually candid incident reports. If you only follow one engineering blog, this is a strong pick.

Long form write ups of decisions taken at a scale most of us will never work at, which is exactly why they are worth reading. Streaming architecture, caching, chaos engineering and personalisation, usually with the numbers and the mistakes included.

A curated set of articles, talks and books about the part of the job that is not writing code: scope, influence, communication and ownership. Useful when you are technically solid, keep getting good reviews, and still cannot work out what is missing for the next level.

Thousands of questions and exercises across Linux, networking, Docker, Kubernetes, CI/CD, cloud, SQL and Terraform, with answers. Good for finding the holes in what you think you know, whether or not there is an interview coming.

The index of every curated awesome list, covering nearly every language, framework and topic in software. When you are starting in an unfamiliar area, finding its awesome list first will usually save you a week of searching.

A directory of free APIs sorted by category, with authentication and CORS support noted for each. The fastest cure for not knowing what to build: pick an API that interests you and make something small with real data instead of another to do list.

A very large, actively maintained index of free books, courses and cheat sheets, organised by language and subject and available in many languages. Check here before buying anything. A surprising number of standard texts are legally free from their authors.

Hundreds of algorithms implemented and readable, in Python and most other languages. Useful in two ways: as a reference when a description in a textbook has not clicked, and as a first open source contribution, because adding a missing algorithm is a genuinely approachable pull request.

Build something real tutorials sorted by language, from a web server in Go to a text editor in C. If you have finished a course and now feel stuck with nothing to make, start here rather than starting another course.

Step by step tutorials for building your own database, git, shell, compiler, docker or operating system from scratch. This is the best answer to the question of what to build when tutorials stop teaching you anything. Pick the one that scares you slightly and give it a month.

A book about how to think about computation rather than how to use a language. It will change how you see abstraction, and it will be hard, and those two facts are related. Free online. Best done slowly with the exercises, alongside a real job rather than instead of one.

Three and a half hours that replace a shelf of blog posts. Karpathy walks the whole training stack, pretraining through post training, and explains why models hallucinate, why they are bad at counting letters, and what a token really is. If you build on top of models, this is the clearest explanation of what is underneath.

The gap between an agent that works in a notebook and one that runs for real is memory, deployment, monitoring, cost control and security. This repository is a set of hands on tutorials for exactly that layer, which almost nothing else covers properly.