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An open GitHub repository from Jane Street with agent skills for AI coding assistants, including a Socratic tutor skill, published with a license and contribution guide.
Google DeepMind describes an agentic framework powered by Gemini Carbon for formal verification of Signal protocol code in Lean, with human experts reviewing specifications. The article is free to read; the achievement is company-reported, and conflicting line counts in its body and metadata should not be treated as an independently verified measure.
Grigory Sapunov describes how AI has changed his coding, research, company administration, reading and schedule. This is a personal account of AI-assisted work, not a representative study of software jobs.
Martin Alderson applies web performance principles to AI agent workflows, covering time to first token, prompt caching and other factors that affect how fast agents complete tasks.
MiniMax’s public model card and downloadable weights for a multimodal mixture-of-experts model supporting text, image, and video inputs. The company describes coding, agent workflows, computer use, and cybersecurity applications and a context window up to one million tokens; its benchmark results are company-reported. Noncommercial use is free under the MiniMax Community License. Commercial use requires attribution and notice, with prior authorization above the license’s revenue threshold; running the model requires suitable computing hardware.
Recursive introduces Flint, a mixture-of-experts coding model with 40 billion total parameters and 2.5 billion active per token, built to run on local hardware. Benchmark results are the company's own claims.
Dominik Picheta describes KillSwitch, an esoteric programming language designed to challenge language models and coding agents, and discusses testing models against it.
Free desktop workspace for coordinating persistent AI coding agents on a local computer. Supports multiple providers and uses the model access or AI plans users already have; it does not include free access to paid models.
Rensselaer Polytechnic Institute's student hackathon, held in person in Troy, NY, on November 7–8, 2026. Registration via Devpost. Devpost page blocked automated checks; hackathons like this normally have no entry fee.
Unblocked's free webinar on giving AI coding agents the right context so they produce mergeable code the first time.
Details: Free to attend, but it is run by Unblocked to show off its own paid product, so expect a pitch. Check the date on their page.
PrettyTable is a free, open-source Python library for drawing formatted ASCII tables in a terminal or text output. This post from Open-source Projects shows what it does and links to the GitHub repo.
Why I recommend it: Free open-source library (MIT license). The link goes to a blog post on opensourceprojects.dev; the project itself lives at github.com/prettytable/prettytable and pypi.org/project/prettytable. The blog runs on ads and sponsorships.
Amazon's agentic coding environment: you write a spec, and its agents plan, build and check code across a codebase. Runs as a desktop app.
From the site: Kiro helps developers and teams do their best work: turn prompts into executable specs, validate code correctness to find bugs unit tests miss, and build across large codebases with parallel agents that learn from every session.
Why I recommend it: Freemium. The free plan gives you 50 credits a month plus access to Claude Sonnet 4.5 and open-weight models, subject to rate limits; paid plans start at $20 a month. Fine for trying agentic coding, not for all-day use.
An open-source platform for running coding agents such as Claude Code and Codex across your own machines and specialising them for domains like CAD, PCBs, robotics and games, with optional open hardware.
From the site: Follow your curiosity. Build across disciplines. Open-source software and hardware for polymaths in the making. - autonomous-ai/openharness
Why I recommend it: The software is free and open source. The agents you run inside it may cost money, and the companion hardware is a separate purchase — the repo itself is the free part.
Anthropic's AI assistant. Strong at long writing, reading documents you paste in, analysis and coding help. Free tier with daily limits; paid plans lift them.
From the site: Claude is Anthropic
Why I recommend it: The one I reach for when the task is writing or thinking through a document. Check anything factual yourself — it can be confidently wrong.
An open-source AI coding assistant that works in your terminal on a real git repository, making commits as it goes. Apache 2.0 licensed.
From the site: aider is AI pair programming in your terminal. Contribute to Aider-AI/aider development by creating an account on GitHub.
Why I recommend it: It edits real files and commits them, so work on a branch. The tool is free; the model you connect it to is not.
An open-source coding assistant for VS Code and JetBrains that you point at any model, including one running locally. Apache 2.0 licensed.
From the site: open-source coding agent. Contribute to continuedev/continue development by creating an account on GitHub.
Why I recommend it: A free alternative to paid coding assistants if you already run a local model. Slower, but it costs nothing per keystroke.
A terminal-based coding agent you run locally to read, write and refactor code from the command line.
From the site: A terminal-based coding agent
Why I recommend it: If you already live in a terminal, this is a lighter way to try agentic coding than a full IDE.
An open format for telling coding agents how to work in your repository, now used by tens of thousands of open-source projects.
From the site: AGENTS.md is a simple, open format for guiding coding agents. Think of it as a README for agents.
Why I recommend it: If you're experimenting with AI coding tools, this is the convention to follow so your instructions actually get read.
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.
Moonshot AI's free Kimi assistant, strong on long documents, research and coding tasks in the browser.
Why I recommend it: Good free option when you need to feed in a long report and get straight answers.
The running record of what changed in each Polytoken release, alongside its free documentation and quickstart.
Why I recommend it: Handy if you use the tool and want to know what broke or improved.
Alibaba's Qwen family of open AI models with a free chat assistant for writing, coding, image and document work in the browser.
Why I recommend it: A strong free alternative when you want a capable assistant without a subscription.
A free local-first AI coding agent that runs as a daemon on your own machine and executes tools against your development environment.
Why I recommend it: Free to use and runs locally, so it is a low-risk way to try agentic coding.
Free OpenRouter developer guide walking through building a terminal-based agent harness — tool calls, loops and model routing — with working code you can adapt.
Why I recommend it: Building a small agent harness yourself is one of the clearest portfolio projects for AI-adjacent roles right now.
XDA Developers had Claude Code (Opus 5), Codex (GPT-5.6) and Google Antigravity (Gemini 3.8) rebuild the same website from the same brief. The comparison shows which agent handles detail, polish and real-world edge cases best.
Why I recommend it: Useful if you are choosing an AI coding assistant for side projects or learning to prompt more effectively. The winner is not necessarily the one you would expect.
A free Claude Code skill where two AI models harden a build plan before any code is written, then swap roles so whoever built it never grades it.
Why I recommend it: A good habit to borrow even outside code: have something other than the author check the plan.
A browser-based AI agent from Sider that lets you customize almost any webpage with plain-language instructions — no coding or extra extensions required.
Why I recommend it: Useful for quick UI tweaks, summarizing comment threads, or reformatting a page while you research.
Free, self-paced certifications in web development, data analysis, machine learning, and more, with hands-on projects.
Why I recommend it: Finish one certification and publish the projects. A completed track with real code beats five half-finished courses on a resume.
Newsletter testing and comparing AI coding tools and prompts, with side-by-side results for developers.
Why I recommend it: Skip the hype cycle and read the comparisons. Pick one tool from a recent test, use it on a real project, and write up what happened.
Top-down deep learning course using PyTorch, covering computer vision, NLP, and model deployment. Assumes existing Python basics.
Why I recommend it: Teaches you to build working models in lesson one instead of six weeks of math first. Best fit if you already know some Python.
Free, project-heavy full-stack web development curriculum.
Why I recommend it: Harder and slower than tutorial sites, and that is the point. You finish with a portfolio, not a playlist.
Free full curriculum in web development, data analysis, and Python with verified certifications.
Why I recommend it: Every certification requires building projects. Those projects are the interview conversation.
Curated coding challenges pulled from real big-tech technical interviews.
Why I recommend it: Work a few problems a day rather than cramming the week before.
The web's largest open-source collection of algorithms across many languages.
Why I recommend it: Read the implementations in the language you interview in.
Anonymous technical mock interviews with experienced engineers.
Why I recommend it: Nothing builds interview calm faster than repeated live practice.
Fast-paced explainers on AI coding tools, developer workflows, and software trends. Hosted by Jeff Delaney.
In plain terms: This YouTube channel offers quick video explainers on software trends, AI coding tools, and developer workflows. You can watch these lessons to stay up to date on modern programming tools and tech industry practices.
Why I recommend it: Fastest way to learn what a tech term actually means.
Nonprofit making STEM careers accessible to young women of color through coding workshops, camps, and hackathons.
Why I recommend it: Share this with any young person in your life who has never been told tech is for them.
