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Release: datasette-mcp 0.2
"rows"fromexecute_sqlis now an array of objects. Previously it was an array of arrays. This should help weaker models avoid losing track of which positional array element maps to which column. #1- Now depends on
mcp>=2.1.1.
This is the first non-alpha release of the plugin. I'm confident it's ready as I've been using it quite a bit myself.
Tags: datasette, model-context-protocol
I was poking around in my ~/.cache/ folder using OmniDiskSweeper when I spotted something interesting. The OpenAI Codex desktop app (since rebranded to just ChatGPT) has 1.7GB of stuff in there in a folder called codex-primary-runtime, including a full Python installation, a full Node.js installation, and native binaries for Poppler, git, and the LibreOffice open source office suite (which forked from OpenOffice.org in 2010):
The ~/.cache/codex-runtimes/codex-primary-runtime/plugins/openai-primary-runtime/plugins/documents folder includes skills which tell Codex how to find and use those binaries.
Tags: codex, generative-ai, openai, ai, llms, openoffice, open-source
They took the letters from me! I have to talk about dwarf behavior now. I can't even talk about dwarf AI. It doesn't exist. It's dwarf behavior, and they misbehave sometimes
— Tarn Adams, co-creator of Dwarf Fortress
Tags: ai, game-design
325 #kakapo! The chicks from this year's record breeding season are now juveniles and so have been added to the population. In 1995 there were just 51 kākāpō left. Recovery of critically endangered species is possible with sustained effort.
— Andrew Digby, providing the best news of the year
Tags: kakapo
It's pretty big: 125B tokens, but only 6B active which means it gets a pretty big performance boost.
I've been trying it out on a DGX Spark using these Unsloth quantized models. I'm still exploring the model - so far I've tried the 72.5GB UD-IQ1_S one (producing these pelicans) and the 78.9GB UD-Q2_K_XL (producing these).
My favorite so far was this xhigh reasoning effort one from UD-Q2_K_XL:
Via Hacker News
Tags: ai, generative-ai, llms, qwen, pelican-riding-a-bicycle, ai-in-china, nvidia-spark
The fact that AI wrote 1M LOC and then refined it over the course of the next couple of months to produce a reliable piece of software that is currently running on millions of developer machines is absolutely mind blowing. And you can say, “well it’s not that impressive because they had an oracle to compare against, so it was simple to go from one language to another”, but I think that’s selling this entire thing short. If you can build a verification system and give proper direction, AI can produce a highly complex, highly sophisticated piece of software and it can continue to refine it until it just works.
— Paul Dix, The end of programming
Tags: coding-agents, ai-assisted-programming, generative-ai, bun, ai, llms
Release: llm-anthropic 0.27
This release mainly provides compatibility with the recently released anthropic v1.0.0 Python library, which switches from httpx to httpx2. OpenAI made the same change in their v3.0.0 release two weeks ago.
Anthropic provide this migration guide for upgrading to 1.0, so I prompted Fable 5 in Claude Code with:
Upgrade to anthropic>=1 - read https://raw.githubusercontent.com/anthropics/anthropic-sdk-python/refs/heads/main/MIGRATION.md and get the tests passing
Here's the resulting PR.
Prior to Fable, it felt silly to waste too much time improving your coding harness or context strategies. A new model would arrive at the same price (or cheaper!) and paper over most of your problems.
But then Fable landed. It was (and still is!) incredible. But the cost was so high and Opus was good enough (as was 5.6, K3, and even GLM) for most of the code we needed.
So we started to think about what work went where.
— Drew Breunig, Fable & The End of the Free Lunch
Tags: drew-breunig, anthropic, claude, llm-pricing, ai, llms, generative-ai, claude-mythos-fable
And this was a debug session from hell, enormously helped by an AI doing much of the grunt-work.
I'd like to call it my tireless helper, but the AI several times stated flat out that this was impossible and unsolvable and that we should just write a report about it.
I suspect those things have been trained by people who may not be quite as stubborn as I am.
But while the AI was ready to give up several times, it did keep adding debug code and analyzing it faithfully when I pushed. So credit where credit is due and I let the AI write the commit message above.
— Linus Torvalds, drm/xe: Don't hand out the flat CCS storage as usable VRAM
Tags: linus-torvalds, linux, generative-ai, ai-assisted-programming, ai, llms
The key skill required to make productive use of coding agents is being able to confidently instruct them on how to make changes and then confidently verify that those changes have been applied in the correct way.
Sometimes this involves reviewing every line of code they have written, but there are other ways to achieve that goal. Eyeballing every line of code has never been the most effective way to validate a chance to a piece of software.
Tags: code-review, coding-agents, generative-ai, agentic-engineering, ai, llms
Release: llm 0.32.1
Fresh installs of LLM stopped working the other day because the OpenAI Python library dropped its usage of httpx, and it turned out LLM depended on that library but only installed it via a transitive openai dependency.
This dot-release fixes that for the moment by pinning to openai<3, and a soon-to-drop 0.33 release will switch from httpx to httpx2.
Release: llm-openrouter 0.7
Now that this plugin is compatible with LLM 0.32 it works much better with reasoning LLMs available through OpenRouter.
- Updated for compatibility with LLM 0.32.
- Models now use OpenRouter's implementation of the Responses API.
- Three new server-side tools: Shell, WebFetch, and WebSearch. Enable these with options like
-T WebSearch.
Tags: llm, openrouter
I wrote about my vibe-coded bandwidth and GPU monitoring macOS task bar apps back in March, and I'm still using both of those on a daily basis.
I'm not habitually knocking out real UIs for my other projects yet, but I'm running out of excuses!
Thomas:
If you haven’t tried your hand at turning one of your 500 throwaway CLIs into a native app, you’re doing yourself a disservice. Go build a native UI. It’ll probably change the way you think.
Tags: thomas-ptacek, ai, generative-ai, llms, vibe-coding, coding-agents
After I released version 1.0, I figured I would have to do the rotations myself. So I sat down with ChatGPT and I didn’t get it to write the code, but I got it to educate me. With a patient, interactive tutor, I was able to finally do what I hadn’t by reading books and asking mathematician friends – I learnt how to use quaternions just enough to make the app work.
So learning doesn’t stop just because I outsource a bunch of thinking to AI. It pushes me to learn more. I like that as an outcome.
— Matt Webb, Galactic Compass 2: now with new augmented reality mode
Tags: matt-webb, generative-ai, chatgpt, education, ai, llms
My hypothesis is that there is a new opportunity for Extensible Software on the web. LLMs radically lower the cost of authoring extensions, and modern sandbox primitives lower the deployment cost and provide good security boundaries. We can build our app as a solid, accountable core, and allow users to safely extend it in many directions by having LLMs fill in the missing pieces. We can give our users super powers.
— Jeremy Morrell, Extensible Software in the age of LLMs
Tags: sandboxing, llms, ai, generative-ai
