Best new learning, design and AI resources: day 29

Best Productivity Resources is twenty-nine days old today. Yesterday brought a strong mix: a full self-study shelf for machine learning, a set of design inspiration and tooling gems, and another wave of AI-agent and self-hosted utilities. Every resource below was reviewed by hand and links directly to its original website or repository.

1. Dive into Deep Learning

Dive into Deep Learning is an interactive open-source book that teaches deep learning with runnable code, math and discussion side by side. It works as a course, a reference and a self-study path. Link: https://github.com/d2l-ai/d2l-en

2. micrograd

micrograd is Andrej Karpathy's tiny autograd engine — a few hundred lines that show exactly how backpropagation works under the hood. The fastest honest way to demystify neural networks. Link: https://github.com/karpathy/micrograd

3. nanoGPT

nanoGPT is the simplest, fastest repository for training and fine-tuning medium-sized GPTs. The codebase is deliberately small and readable, which makes it a superb learning tool. Link: https://github.com/karpathy/nanoGPT

4. Neural Networks: Zero to Hero

Zero to Hero is Karpathy's video course that builds neural networks from scratch, step by step, ending with a GPT. Pair it with micrograd and nanoGPT for the full path. Link: https://github.com/karpathy/nn-zero-to-hero

5. Mathematics for Machine Learning

Mathematics for ML is the free companion book covering the linear algebra, calculus and probability you actually need for machine learning. Read it alongside a practical course. Link: https://github.com/mml-book/mml-book.github.io

6. Stanford CS 229 Machine Learning cheatsheets

Afshine Amidi's famous CS 229 cheatsheets compress an entire Stanford machine-learning course into a handful of dense, printable references. Link: https://github.com/afshinea/stanford-cs-229-machine-learning

7. ML From Scratch

ML From Scratch implements classic machine-learning algorithms in plain Python with minimal dependencies, so you can read exactly how each one works. Link: https://github.com/eriklindernoren/ML-From-Scratch

8. Detail

Detail is a beautifully crafted design resource for people who care about interfaces — sharp curation and presentation that reward slow browsing. Link: https://detail.design/

9. Toolcraft

Toolcraft is an open-source project from Pixel Point for building your own design apps with AI — a practical starting point if you want to ship a niche design tool. Link: https://github.com/pixel-point/toolcraft

10. Pryzm

Pryzm is a background and visual studio for designers that runs entirely in the browser, handy for gradients, textures and quick visual experiments. Link: https://pryzm.design/

11. Valessa

Valessa, built by Riotters, is a 3D product visualizer for creating polished product shots and scenes without a full 3D pipeline. Link: https://valessa.riotters.com/

12. Book of Shapes

Book of Shapes is a curated gallery of generative patterns — a calm, endlessly browsable source of visual inspiration. Link: https://bookofshapes.com/

13. Iconly

Iconly is an inspiration library of more than 2,400 icons from apps, games and web apps, organised for quick reference when you are designing interfaces. Link: https://iconly.design/

14. Stop Slop

Stop Slop is a skill file that teaches AI agents to remove the usual AI tells from prose — useful if you draft with a model and want writing that reads human. Link: https://github.com/hardikpandya/stop-slop

15. Speakr

Speakr is a self-hosted audio transcription app for turning recordings into searchable text on your own hardware. Link: https://github.com/murtaza-nasir/speakr

16. AgentGlass

AgentGlass puts every AI coding agent you run on one screen, with live cost and token tracking — a practical observability layer for multi-agent work. Link: https://github.com/SirAllap/agentglass

17. Compass

Compass is a local-first knowledge graph engine for code written in Rust, giving agents and developers a structural map of a codebase. Link: https://github.com/crabbuild/compass

18. Claude Deep Research Skill

Claude Deep Research Skill is an eight-phase, enterprise-grade research workflow packaged as a Claude Code skill. Link: https://github.com/199-biotechnologies/claude-deep-research-skill

19. brag

brag is a command-line tool that turns a project into a shareable launch video with a single command — great for shipping days. Link: https://github.com/latent-spaces/brag

20. StateWave

StateWave explores modern state management patterns for developers who want predictable, maintainable application state. Link: https://github.com/smaramwbc/statewave

Also added yesterday

• MatrixOne — a cloud-native database unifying transactional, analytical and AI workloads: https://github.com/matrixorigin/matrixone

• Claude Ops — operations tooling for Claude-centric workflows: https://github.com/Lifecycle-Innovations-Limited/claude-ops

• slackcli — a command-line client for Slack power users: https://github.com/shaharia-lab/slackcli

• The Art of Command Line — the classic one-page mastery guide: https://github.com/jlevy/the-art-of-command-line

• Beam Weaver — Elixir-native LangChain/LangGraph-style agent tooling: https://github.com/caudena/beam_weaver

• Build World — interactive 3D worlds with your AI agent: https://github.com/thrixel/build-world

• Pretty Mermaid Skills — beautiful Mermaid diagrams as SVG or terminal ASCII: https://github.com/imxv/Pretty-mermaid-skills

• gpty — a Godot-based Rust multi-PTY emulator: https://github.com/godot-pty/gpty

• Ossium, Mimik, Raven, agtx, ModelScope Cookbook, Cybersecurity Projects, Swarm, Redamon, Portracker, Oya Browser, BrainAPI and vphone-ws — a fresh batch of self-hosted, systems and AI utilities now searchable in the directory.

That is the full set for day 29. Every addition is live in the directory with categories, best-for tags and pricing, and each links straight to the source.