Things I Learned - 28 Jun 2026

[Anand S]

This week, I learned:

• Every Substack feed has an RSS feed at https://your.substack.com/feed. Substack help. I used this to scan my browsing history to identify Substacks I visit - and subscribed to Marcus on AI - an AI sceptic AI asked me to read about.
• Cloudflare let's agents create temporary accounts so that they can deploy and test. Enables trial and error - a powerful capability.
• "They're on mobile but this is substantiative enough to warrant length." I spotted this in Claude's thinking when prompting on mobile. So, if I ask Claude something on mobile, it will give me shorter responses by default. Clever design - but something to keep in mind. If I want some heavy thinking done by Claude, better to do it on desktop than try to give it conflicting instructions.
• Giant Permissive Image Corpus (GPIC) has 100 million Qwen tagged public images. Even as a simple searchable image catalog this has value. Jeff Clark - Import AI
• Ethan Mollick had an agent test his book summary against multiple LLMs as readers to find out how they would recommend it - and optimized. This is a great practical use of agents as consumers, and material for my When Data is for Agents, Not Humans workshop.
• kage is an easy CLI to clone websites and read offline. For example, kage clone https://simonwillison.net/2026/Jun/ -o ~/tmp/site --scope-prefix /2026/Jun/ --max-depth 1 clones all Jun 2026 articles from Simon Willison's blog. Then kage serve ~/tmp/site serves it locally. While it's easy, the only time I need this is on a flight, and in that case, a local RSS feed app works better. I'm using newsboat for that.
• To me, the clearest sign of AI writing from the Wikipedia:AI or not quiz was consistent paragraph lengths. I got the first 3/3 wrong, but once I used this heuristic, I got 6/7 right. Updated my LLM Smells.
• The files .git/info/exclude and ~/.config/git/ignore are also ignored by git, like .gitignore, but useful if you don't want to commit them into the .gitignore file. For example, .DS_Store makes sense only for Mac machines, not each repo. .vscode/ makes sense only for VS Code users. Nelson Figueroa
• Justin Poehnelt, author of the brilliant Google Workspace CLI gws, was fired for it. There have been no updates for 3 months, but none may be required - it feels perfect. X
• Lore is a centralized version control system for large binaries. If you have large binaries (e.g. images, videos, ...) that multiple people edit, it's better than Git LFS or Perforce. ChatGPT
• Deno Desktop lets you use JS to build desktop apps. I tried it. It's easy to install, compact to code, leverages familar web technology, and compiles to multi-platform binary. The binaries are a bit larger than I'd like, though - 80MB for a Hello World on Linux/Windows and ~70MB on Mac.
• Codex reported that You have 2 usage limit resets available. Run /usage to use one. This thread has context. After resetting, the next reset might be 7 days after the reset, though (source).
• After having a child, fathers are affected biologically, too. Testosterone drops, cortisol & prolactin & estrogen rise, the brain rewires for empathy and threat detection - and of course, there's less sleep. These sometimes lead to "Paternal Postpartum Depression" - something I didn't even know was a thing. The havoc kids wreak upon us! 🙂 Gemini
• With AI writing more code, formal code proofs are becoming more accessible. You just need to ask a coding agent to prove / disprove a function. You can use:
  • Z3 to find/prove whether a counterexample exists. Best default.
  • Dafny to prove that code obeys a spec. Best for real algorithmic code.
  • Alloy to find loopholes in relational models, schemas, permissions, and workflows. Best for data.
  • TLA+ to check whether stateful, concurrent, or agentic systems can evolve into a bad state. Best for systems / workflows.
  • .. and there's a long tail of these.
• Python is named after Monty Python, not the snake. I knew this, but forgot!
• Python now has multiple cross-platform app paths: PyInstaller and Nuitka for executables, Kivy, Flet, and BeeWare/Briefcase for GUI/mobile/desktop apps, and PyScript/Pyodide for browser/WASM apps - a route that became more serious because Pyodide-compatible WebAssembly wheels can now be published directly to PyPI.
• On the one hand, AI is writing code, so there's no point learning Python. On the other hand, AI is writing code mostly in Python - so THAT's what you need to learn more. I think we should teach Python using AI, that is, teach how to write and debug Python code using AI. That'll end up teaching skills people will really need.
• Computational thinking = Decomposition + Abstraction + Algorithm design + Pattern recognition.
  In AI, that translates to = Framing + Context engineering + Orchestration (harness engineering?) + Verification design. Maybe I'd add Assetization / Systems.