2026-02-07 02:44:21
An ominous headline to see on the official Heroku blog and yes, it's bad news.
Today, Heroku is transitioning to a sustaining engineering model focused on stability, security, reliability, and support. Heroku remains an actively supported, production-ready platform, with an emphasis on maintaining quality and operational excellence rather than introducing new features. We know changes like this can raise questions, and we want to be clear about what this means for customers.
Based on context I'm guessing a "sustaining engineering model" (this definitely isn't a widely used industry term) means that they'll keep the lights on and that's it.
This is a very frustrating piece of corporate communication. "We want to be clear about what this means for customers" - then proceeds to not be clear about what this means for customers.
Why are they doing this? Here's their explanation:
We’re focusing our product and engineering investments on areas where we can deliver the greatest long-term customer value, including helping organizations build and deploy enterprise-grade AI in a secure and trusted way.
My blog is the only project I have left running on Heroku. I guess I'd better migrate it away (probably to Fly) before Salesforce lose interest completely.
Tags: salesforce, heroku, fly
2026-02-06 08:42:22
When I want to quickly implement a one-off experiment in a part of the codebase I am unfamiliar with, I get codex to do extensive due diligence. Codex explores relevant slack channels, reads related discussions, fetches experimental branches from those discussions, and cherry picks useful changes for my experiment. All of this gets summarized in an extensive set of notes, with links back to where each piece of information was found. Using these notes, codex wires the experiment and makes a bunch of hyperparameter decisions I couldn’t possibly make without much more effort.
— Karel D'Oosterlinck, I spent $10,000 to automate my research at OpenAI with Codex
Tags: codex-cli, coding-agents, ai-assisted-programming, generative-ai, openai, ai, llms
2026-02-06 07:39:07
Mitchell Hashimoto: My AI Adoption Journey
Some really good and unconventional tips in here for getting to a place with coding agents where they demonstrably improve your workflow and productivity. I particularly liked:Reproduce your own work - when learning to use coding agents Mitchell went through a period of doing the work manually, then recreating the same solution using agents as an exercise:
I literally did the work twice. I'd do the work manually, and then I'd fight an agent to produce identical results in terms of quality and function (without it being able to see my manual solution, of course).
End-of-day agents - letting agents step in when your energy runs out:
To try to find some efficiency, I next started up a new pattern: block out the last 30 minutes of every day to kick off one or more agents. My hypothesis was that perhaps I could gain some efficiency if the agent can make some positive progress in the times I can't work anyways.
Outsource the Slam Dunks - once you know an agent can likely handle a task, have it do that task while you work on something more interesting yourself.
Via Hacker News
Tags: ai, generative-ai, llms, ai-assisted-programming, mitchell-hashimoto, coding-agents
2026-02-06 04:29:20
Two major new model releases today, within about 15 minutes of each other.
Anthropic released Opus 4.6. Here's its pelican:
OpenAI release GPT-5.3-Codex, albeit only via their Codex app, not yet in their API. Here's its pelican:
I've had a bit of preview access to both of these models and to be honest I'm finding it hard to find a good angle to write about them - they're both really good, but so were their predecessors Codex 5.2 and Opus 4.5. I've been having trouble finding tasks that those previous models couldn't handle but the new ones are able to ace.
The most convincing story about capabilities of the new model so far is Nicholas Carlini from Anthropic talking about Opus 4.6 and Building a C compiler with a team of parallel Claudes - Anthropic's version of Cursor's FastRender project.
Tags: llm-release, anthropic, generative-ai, openai, pelican-riding-a-bicycle, ai, llms, parallel-agents, c, nicholas-carlini
2026-02-05 08:23:38
Spotlighting The World Factbook as We Bid a Fond Farewell
Somewhat devastating news today from CIA:One of CIA’s oldest and most recognizable intelligence publications, The World Factbook, has sunset.
There's not even a hint as to why they decided to stop maintaining this publication, which has been their most useful public-facing initiative since 1971 and a cornerstone of the public internet since 1997.
In a bizarre act of cultural vandalism they've not just removed the entire site (including the archives of previous versions) but they've also set every single page to be a 302 redirect to their closure announcement.
The Factbook has been released into the public domain since the start. There's no reason not to continue to serve archived versions - a banner at the top of the page saying it's no longer maintained would be much better than removing all of that valuable content entirely.
Up until 2020 the CIA published annual zip file archives of the entire site. Those are available (along with the rest of the Factbook) on the Internet Archive.
I downloaded the 384MB .zip file for the year 2020 and extracted it into a new GitHub repository, simonw/cia-world-factbook-2020. I've enabled GitHub Pages for that repository so you can browse the archived copy at simonw.github.io/cia-world-factbook-2020/.
Here's a neat example of the editorial voice of the Factbook from the What's New page, dated December 10th 2020:
Years of wrangling were brought to a close this week when officials from Nepal and China announced that they have agreed on the height of Mount Everest. The mountain sits on the border between Nepal and Tibet (in western China), and its height changed slightly following an earthquake in 2015. The new height of 8,848.86 meters is just under a meter higher than the old figure of 8,848 meters. The World Factbook rounds the new measurement to 8,849 meters and this new height has been entered throughout the Factbook database.
Via Hacker News
Tags: cia, github, internet-archive
2026-02-05 06:42:34
Voxtral transcribes at the speed of sound
Mistral just released Voxtral Transcribe 2 - a family of two new models, one open weights, for transcribing audio to text. This is the latest in their Whisper-like model family, and a sequel to the original Voxtral which they released in July 2025.Voxtral Realtime - official name Voxtral-Mini-4B-Realtime-2602 - is the open weights (Apache-2.0) model, available as a 8.87GB download from Hugging Face.
You can try it out in this live demo - don't be put off by the "No microphone found" message, clicking "Record" should have your browser request permission and then start the demo working. I was very impressed by the demo - I talked quickly and used jargon like Django and WebAssembly and it correctly transcribed my text within moments of me uttering each sound.
The closed weight model is called voxtral-mini-latest and can be accessed via the Mistral API, using calls that look something like this:
curl -X POST "https://api.mistral.ai/v1/audio/transcriptions" \
-H "Authorization: Bearer $MISTRAL_API_KEY" \
-F model="voxtral-mini-latest" \
-F file=@"Pelican talk at the library.m4a" \
-F diarize=true \
-F context_bias="Datasette" \
-F timestamp_granularities="segment"It's priced at $0.003/minute, which is $0.18/hour.
The Mistral API console now has a speech-to-text playground for exercising the new model and it is excellent. You can upload an audio file and promptly get a diarized transcript in a pleasant interface, with options to download the result in text, SRT or JSON format.
Via Hacker News
Tags: ai, generative-ai, llms, hugging-face, mistral, speech-to-text
