Release: datasette-ports 0.1

Another example of README-driven development, this time solving a problem that might be unique to me.

I often find myself running a bunch of different Datasette instances with different databases and different in-development plugins, spreads across dozens of different terminal windows - enough that I frequently lose them!

Now I can run this:

datasette install datasette-ports
datasette ports

And get a list of every running instance that looks something like this:

http://127.0.0.1:8333/ - v1.0a26
  Databases: data
  Plugins: datasette-enrichments, datasette-enrichments-llm, datasette-llm, datasette-secrets
http://127.0.0.1:8001/ - v1.0a26
  Databases: creatures
  Plugins: datasette-extract, datasette-llm, datasette-secrets
http://127.0.0.1:8900/ - v0.65.2
  Databases: logs

Tags: datasette

Eight years of wanting, three months of building with AI Lalit Maganti provides one of my favorite pieces of long-form writing on agentic engineering I've seen in ages. They spent eight years thinking about and then three months building syntaqlite, which they describe as "h...

From anonymized U.S. ChatGPT data, we are seeing:

• ~2M weekly messages on health insurance
• ~600K weekly messages [classified as healthcare] from people living in “hospital deserts” (30 min drive to nearest hospital)
• 7 out of 10 msgs happen outside clinic hours

— Chengpeng Mou, Head of Business Finance, OpenAI

Tags: ai-ethics, generative-ai, openai, chatgpt, ai, llms

Tool: Syntaqlite Playground

Lalit Maganti's syntaqlite is currently being discussed on Hacker News thanks to Eight years of wanting, three months of building with AI, a deep dive into exactly how it was built.

This inspired me to revisit a research project I ran when Lalit first released it a couple of weeks ago, where I tried it out and then compiled it to a WebAssembly wheel so it could run in Pyodide in a browser (the library itself uses C and Rust).

This new playground loads up the Python library and provides a UI for trying out its different features: formating, parsing into an AST, validating, and tokenizing SQLite SQL queries.

Tags: sql, ai-assisted-programming, sqlite, tools, agentic-engineering

Release: scan-for-secrets 0.2

• CLI tool now streams results as they are found rather than waiting until the end, which is better for large directories.
• -d/--directory option can now be used multiple times to scan multiple directories.
• New -f/--file option for specifying one or more individual files to scan.
• New scan_directory_iter(), scan_file() and scan_file_iter() Python API functions.
• New -v/--verbose option which shows each directory that is being scanned.

Release: scan-for-secrets 0.1.1

• Added documentation of the escaping schemes that are also scanned.
• Removed unnecessary repr escaping scheme, which was already covered by json.

Release: scan-for-secrets 0.1 I like publishing transcripts of local Claude Code sessions using my claude-code-transcripts tool but I'm often paranoid that one of my API keys or similar secrets might inadvertently be revealed in the detailed log files. I built this new P...

Release: research-llm-apis 2026-04-04

I'm working on a major change to my LLM Python library and CLI tool. LLM provides an abstraction layer over hundreds of different LLMs from dozens of different vendors thanks to its plugin system, and some of those vendors have grown new features over the past year which LLM's abstraction layer can't handle, such as server-side tool execution.

To help design that new abstraction layer I had Claude Code read through the Python client libraries for Anthropic, OpenAI, Gemini and Mistral and use those to help craft curl commands to access the raw JSON for both streaming and non-streaming modes across a range of different scenarios. Both the scripts and the captured outputs now live in this new repo.

Tags: llm, apis, json, llms

[GitHub] platform activity is surging. There were 1 billion commits in 2025. Now, it's 275 million per week, on pace for 14 billion this year if growth remains linear (spoiler: it won't.)

GitHub Actions has grown from 500M minutes/week in 2023 to 1B minutes/week in 2025, and now 2.1B minutes so far this week.

— Kyle Daigle, COO, GitHub

Tags: github, github-actions

Vulnerability Research Is Cooked Thomas Ptacek's take on the sudden and enormous impact the latest frontier models are having on the field of vulnerability research. Within the next few months, coding agents will drastically alter both the practice and the economics of expl...

A fun thing about recording a podcast with a professional like Lenny Rachitsky is that his team know how to slice the resulting video up into TikTok-sized short form vertical videos. Here's one he shared on Twitter today which ended up attracting over 1.1m views!

That was 48 seconds. Our full conversation lasted 1 hour 40 minutes.

Tags: ai-ethics, coding-agents, agentic-engineering, generative-ai, podcast-appearances, ai, llms, cognitive-debt

On the kernel security list we've seen a huge bump of reports. We were between 2 and 3 per week maybe two years ago, then reached probably 10 a week over the last year with the only difference being only AI slop, and now since the beginning of the year we're around 5-10 per day depending on the days (fridays and tuesdays seem the worst). Now most of these reports are correct, to the point that we had to bring in more maintainers to help us.

And we're now seeing on a daily basis something that never happened before: duplicate reports, or the same bug found by two different people using (possibly slightly) different tools.

— Willy Tarreau, Lead Software Developer. HAPROXY

Tags: security, linux, generative-ai, ai, llms, ai-security-research

The challenge with AI in open source security has transitioned from an AI slop tsunami into more of a ... plain security report tsunami. Less slop but lots of reports. Many of them really good.

I'm spending hours per day on this now. It's intense.

— Daniel Stenberg, lead developer of cURL

Tags: daniel-stenberg, security, curl, generative-ai, ai, llms, ai-security-research

Months ago, we were getting what we called 'AI slop,' AI-generated security reports that were obviously wrong or low quality. It was kind of funny. It didn't really worry us.

Something happened a month ago, and the world switched. Now we have real reports. All open source projects have real reports that are made with AI, but they're good, and they're real.

— Greg Kroah-Hartman, Linux kernel maintainer (bio), in conversation with Steven J. Vaughan-Nichols

Tags: security, linux, generative-ai, ai, llms, ai-security-research

Research: Can JavaScript Escape a CSP Meta Tag Inside an Iframe?

In trying to build my own version of Claude Artifacts I got curious about options for applying CSP headers to content in sandboxed iframes without using a separate domain to host the files. Turns out you can inject <meta http-equiv="Content-Security-Policy"...> tags at the top of the iframe content and they'll be obeyed even if subsequent untrusted JavaScript tries to manipulate them.

Tags: iframes, security, javascript, content-security-policy, sandboxing

The Axios team have published a full postmortem on the supply chain attack which resulted in a malware dependency going out in a release the other day, and it involved a sophisticated social engineering campaign targeting one of their maintainers directly. Here's Jason Saaym...

I was a guest on Lenny Rachitsky's podcast, in a new episode titled An AI state of the union: We've passed the inflection point, dark factories are coming, and automation timelines. It's available on YouTube, Spotify, and Apple Podcasts. Here are my highlights from our conve...

Gemma 4: Byte for byte, the most capable open models Four new vision-capable Apache 2.0 licensed reasoning LLMs from Google DeepMind, sized at 2B, 4B, 31B, plus a 26B-A4B Mixture-of-Experts. Google emphasize "unprecedented level of intelligence-per-parameter", providing yet ...

Release: llm-gemini 0.30

New models gemini-3.1-flash-lite-preview, gemma-4-26b-a4b-it and gemma-4-31b-it. See my notes on Gemma 4.

Tags: gemini, llm, gemma

I just sent the March edition of my sponsors-only monthly newsletter. If you are a sponsor (or if you start a sponsorship now) you can access it here. In this month's newsletter:

• More agentic engineering patterns
• Streaming experts with MoE models on a Mac
• Model releases in March
• Vibe porting
• Supply chain attacks against PyPI and NPM
• Stuff I shipped
• What I'm using, March 2026 edition
• And a couple of museums

Here's a copy of the February newsletter as a preview of what you'll get. Pay $10/month to stay a month ahead of the free copy!

Tags: newsletter

Release: datasette-llm 0.1a6

• The same model ID no longer needs to be repeated in both the default model and allowed models lists - setting it as a default model automatically adds it to the allowed models list. #6
• Improved documentation for Python API usage.

Tags: llm, datasette

Release: datasette-enrichments-llm 0.2a1

• The actor who triggers an enrichment is now passed to the llm.mode(... actor=actor) method. #3

Tags: enrichments, llm, datasette

Release: datasette-extract 0.3a0

• This plugin now uses datasette-llm to configure and manage models. This means it's possible to specify which models should be made available for enrichments, using the new enrichments purpose.

Tags: llm, datasette

Release: datasette-enrichments-llm 0.2a0

• This plugin now uses datasette-llm to configure and manage models. This means it's possible to specify which models should be made available for enrichments, using the new enrichments purpose.

Tags: llm, datasette

Release: datasette-llm-usage 0.2a0

• Removed features relating to allowances and estimated pricing. These are now the domain of datasette-llm-accountant.
• Now depends on datasette-llm for model configuration. #3
• Full prompts and responses and tool calls can now be logged to thellm_usage_prompt_log table in the internal database if you set the new datasette-llm-usage.log_prompts plugin configuration setting.
• Redesigned the /-/llm-usage-simple-prompt page, which now requires the llm-usage-simple-prompt permission.

Tags: llm, datasette

Release: datasette-llm 0.1a5

• The llm_prompt_context() plugin hook wrapper mechanism now tracks prompts executed within a chain as well as one-off prompts, which means it can be used to track tool call loops. #5

Tags: llm, datasette

I want to argue that AI models will write good code because of economic incentives. Good code is cheaper to generate and maintain. Competition is high between the AI models right now, and the ones that win will help developers ship reliable features fastest, which requires simple, maintainable code. Good code will prevail, not only because we want it to (though we do!), but because economic forces demand it. Markets will not reward slop in coding, in the long-term.

— Soohoon Choi, Slop Is Not Necessarily The Future

Tags: slop, ai-assisted-programming, generative-ai, agentic-engineering, ai, llms

Supply Chain Attack on Axios Pulls Malicious Dependency from npm

Useful writeup of today's supply chain attack against Axios, the HTTP client NPM package with 101 million weekly downloads. Versions 1.14.1 and 0.30.4 both included a new dependency called plain-crypto-js which was freshly published malware, stealing credentials and installing a remote access trojan (RAT).

It looks like the attack came from a leaked long-lived npm token. Axios have an open issue to adopt trusted publishing, which would ensure that only their GitHub Actions workflows are able to publish to npm. The malware packages were published without an accompanying GitHub release, which strikes me as a useful heuristic for spotting potentially malicious releases - the same pattern was present for LiteLLM last week as well.

Via lobste.rs

Tags: javascript, security, npm, supply-chain

Release: datasette-llm 0.1a4

• Ability to configure different API keys for models based on their purpose - for example, set it up so enrichments always use gpt-5.4-mini with an API key dedicated to that purpose. #4

I released llm-echo 0.3 to provide an API key testing utility I needed for the tests for this new feature.

Tags: llm, datasette

Release: llm-all-models-async 0.1

LLM plugins can define new models in both sync and async varieties. The async variants are most common for API-backed models - sync variants tend to be things that run the model directly within the plugin.

My llm-mrchatterbox plugin is sync only. I wanted to try it out with various Datasette LLM features (specifically datasette-enrichments-llm) but Datasette can only use async models.

So... I had Claude spin up this plugin that turns sync models into async models using a thread pool. This ended up needing an extra plugin hook mechanism in LLM itself, which I shipped just now in LLM 0.30.

Tags: llm, async, python