2467 hand-picked resources, updated every week. Search it, filter it, or just browse a collection and see what catches your eye. Want today’s headlines instead? Read the free AI news feed.
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Answers come only from resources in this hub, with the sources listed underneath.
Axon's own documentation for its policing technology, covering AI features, body cameras, software, robotics, TASER devices and VR training. Free to read.
From the site: Explore Axon product guides by technology area, including AI, cameras, software, robotics, TASER weapons, and VR training.
Why I recommend it: Worth reading if you want to know what police surveillance and AI tools actually do, in the vendor's own words. This is company documentation, not an independent assessment.
Free, well-written documentation and tutorials for building and hosting sites, APIs and AI workers — one of the better free places to learn modern web infrastructure.
From the site: Connect, protect, and build everywhere.
Why I recommend it: Free docs with working examples. A good self-teaching path if you want infrastructure skills on your resume.
GitHub's free article library explaining version control, DevOps, CI/CD, security practices and AI-assisted development in plain terms.
From the site: GitHub is where people build software. More than 150 million people use GitHub to discover, fork, and contribute to over 420 million projects.
Why I recommend it: Good plain-English explainers for the terms that show up in job descriptions — read the DevOps and CI/CD ones before an interview.
The official free React docs, including the interactive "Learn React" course that teaches components, state and hooks from scratch with in-browser exercises.
From the site: React is the library for web and native user interfaces. Build user interfaces out of individual pieces called components written in JavaScript. React is designed to let you seamlessly combine components written by independent people, teams, and organizations.
Why I recommend it: If you want to build web interfaces, start with the official tutorial rather than a paid bootcamp — it is free and better maintained.
Free public documentation explaining how an autonomous AI software engineer plans, runs and reviews coding work, including its limits and where human review is required.
From the site: Devin is the AI software engineer, built to help ambitious engineering teams crush their backlogs.
Why I recommend it: The product costs money but the docs are free — read them to understand what "AI engineer" tools actually do and do not do before anyone tells you your job is gone.
The stewards of the Open Source Definition, with plain-language explanations of every approved licence and guidance on choosing one for your own project.
Why I recommend it: Read this before you publish code or a template — the license you pick decides what others can legally do with your work.
The official home of Rust, with the free online book, guided tutorials, standard library docs and installer for a memory-safe systems language used across infrastructure and AI tooling.
Why I recommend it: Everything you need to learn Rust is free here — start with "The Book," it is one of the best free programming texts online.
A free open format for writing structured assumptions and requirements next to the code itself, so AI coding agents build against stated rules rather than guesses.
Why I recommend it: Relevant even if you do not write code: it is a clear example of writing requirements precisely enough that a machine can follow them.
HashiCorp's free documentation, hands-on tutorials and sandbox for Terraform, the infrastructure-as-code tool used to build and version cloud infrastructure across AWS, Azure, Google Cloud, Oracle Cloud and Docker.
Why I recommend it: Free, official, step-by-step tutorials — one of the fastest ways to get a real cloud skill on your resume without paying for a course.
The open-source Python library for static, animated and interactive charts, with free plot-type galleries, tutorials, cheat sheets and a full API reference.
Why I recommend it: If you are learning data work, start here: the example gallery lets you copy a chart that already looks like what you need and adapt it.
A free agent skill that turns a codebase or a plain-English system description into an interactive architecture, workflow, sequence or data-flow diagram you can share as a single file.
Why I recommend it: Handy for explaining how something works in an interview or a proposal without hand-drawing diagrams.
A research paper describing a software library whose repository holds almost no code: plain-language design documents are the durable artifact, and AI coding agents regenerate the implementation from those docs on every update.
Why I recommend it: The takeaway for non-engineers is bigger than the paper: clear written thinking is becoming the valuable skill, and the code is what gets generated from it.
The official documentation and tutorials for Python's core machine learning library.
In plain terms: This website provides official guides and examples for a popular Python machine learning library. You can use it to learn data analysis, sort information, and build predictive models to build your technical skills.
Why I recommend it: If you say data science on your resume, you should be able to work through these examples.
