Most of Europe has not yet absorbed what AI is about to do to us. The few who have are not saying it loudly enough.
We wrote Europe 2031: a five-year scenario of the continent's slide into irrelevance, how AI is driving it, and what can still be done to change course.
it's not done if it's not implemented
it's not done if the implementation is ugly
it's not done if it's not documented
it's not done if users can't discover it
it's not done if you can't market it
I want some kind of LLM workflow tool.
• Ability to manage a set of input files (Markdown or similar), plus other general-purpose context.
• With real-time collaboration. (And maybe some concept of snapshots or VCS integration.)
• And the ability to create/manage a inference workflows and a stored set of prompts.
• Access to general-purpose coding agents (and not just chat models).
• Some concept of compiled outputs/inference results (which ideally can be shared externally).
Many projects have this feeling: "there is all this stuff, which I want to process/compute over in this iterated way, with some build artifacts being important/worth saving." GNU Autotools x Notion or something. Is anyone building this?
We’ve automated every single thing we can @every with AI agents.
And yet there’s way more human work to do than ever. We’ve gone from 4 -> 30 human employees since GPT-3.
I wrote a report on the structural reasons: how AI makes expert competence cheap, why that drives up demand for experts, and why the dynamic only intensifies as we approach AGI.
After Automation: https://t.co/Lb7SUCduAg
recommended reading. i really like the durability aspect of dynamic workflows. looked into how it's implemented, and while there are some minor footguns, it's smart!
Today at 4pm PT @HamelHusain is going to show us how he uses agents to build and he's also going to warn us about serious failure modes.
He sent me this demo video asking if this is ok to show live. Is it?
Register to join live or get the recording afterwards: https://t.co/D0z87OLoPd
the cynic in me says this isn't the full story. the techie kid in me says "woahhhh, we're gonna science way harder in the future via fruitful AI assistance/collaboration"
Attempted to write a Steam Engine hype at the era of Industrial Revolution as if it was the age of AI —
The steam engine breakthrough is insane right now.
Watt’s separate condenser + new GRPO optimization just dropped the 405 hp-class engine. We went from 7 hp → 70 hp → 405 hp+ in basically three years. One machine now does the work of 50+ men or water wheels — nonstop, rain or shine, anywhere.
Textile mills, ironworks, everything scaling 5-10x overnight. Productivity exploding.
This isn’t incremental. It’s automating physical labor at massive scale. Jobs shifting forever. Society about to look unrecognizable.
The Industrial Revolution isn’t coming. It’s here and accelerating faster than anyone predicted.
Terrified. Excited. Both.
What a time to be alive. 🚂💨
if you look around you can see everyone is completely confused about whether
one: every product needs an agent
or two: every product needs to plug into an agent users are already using
everyone picking 1 or 2 and building infra for that and praying they're right
I packaged up the "autoresearch" project into a new self-contained minimal repo if people would like to play over the weekend. It's basically nanochat LLM training core stripped down to a single-GPU, one file version of ~630 lines of code, then:
- the human iterates on the prompt (.md)
- the AI agent iterates on the training code (.py)
The goal is to engineer your agents to make the fastest research progress indefinitely and without any of your own involvement. In the image, every dot is a complete LLM training run that lasts exactly 5 minutes. The agent works in an autonomous loop on a git feature branch and accumulates git commits to the training script as it finds better settings (of lower validation loss by the end) of the neural network architecture, the optimizer, all the hyperparameters, etc. You can imagine comparing the research progress of different prompts, different agents, etc.
https://t.co/YCvOwwjOzF
Part code, part sci-fi, and a pinch of psychosis :)
🔥New T7 Policy Brief on "Addressing the Debt Crisis in the Global South: Debt Relief for Sustainable Recoveries"
Download here: https://t.co/p5CfyIWMjZ