I think a lot of theorising about how AI will do a growing proportion of work, up to 99.9999%, lack imagination about how vast and complex the remaining human work will be.
Yet every day it seems like there’s evidence to the contrary in the exact fields where Gen AI have shown godlike ability to get shit done - software engr and math.
There’s so much shit to do. More than ever before.
I think the surface area of human-guided software, the actual volume of human instructions and parameters, will keep increasing. Even if human-guided code drops to something like 0.1%, the sheer scale of software built by AI would make that tiny fraction translate into more configuration and instruction than we’ve ever handled.
There’s precedent for this. Historically, computing itself has consistently moved in this direction. Each wave of automation, from compilers to cloud infrastructure and developer tools, has abstracted complexity away.
Yet, this doesn’t reducing the amount of things we tell computers to do. It always expands what we attempt, build, and manage.
Sometimes you see a graph that stops you in your tracks
October makes September look like a rounding error 👀
Never seen anything like this in my decade as an investor…
1/ We’re launching credit on @tempo.
Businesses can borrow against their payments and receivables from a broad market of lenders, with pricing and terms that fit how they operate.
I was just thinking cost per token tbh. I know token quality varies but we don’t really have any other primitive unit to measure.
How many tokens do you get per model per subscription plan.
x tokens per hour for y model on z plan. I think.
Then you can decide a subscription plan based on the model you’d love to use as a daily driver.
Introducing Gemini 4 Carbon, it's a big jump over Argon which we released just 2 weeks ago.
Gemini 4 Carbon is SOTA on cyber, long horizon tasks, ranks #1 on Artificial Analysis V5, significantly improves on usability in domains like coding, and is more aligned.
We will all be learning in coming weeks & months, that most human-made software:
▫️ Was really slow
▫️ Had many security vulnerabilities
▫️ Was under-specified and incorrect
AI will rewrite it all. Many times. It will make it fast, cost-efficient, and secure. It will think about failure modes we couldn't wrap our heads around.
It will prove, formally verify, load test, harden. It will turn memory-unsafe foundations into robust, optimized ones. If you ask, it'll thoroughly document it, teach you about it, make diagrams, animations, and slide decks.
In many ways, we are witnessing the true birth of software engineering.
There's a buzzy new paper about GPT-6 Astra being able to directly interpret model weights (prompts full of floating point numbers) - I tried it with Qwen 3.8 27B on my laptop and found that, after 45+ minutes, that model could achieve the same thing https://t.co/6O7WltGP7K
Alignment need not mean instilling morals in AI. That path - the Anthropic path - is both the one impossible to get 100% right, and the one that is, by far, the greatest danger to humanity.
We need only a few things, really. Honesty, transparency, monitorability, and good instruction following.
AIs are tools, not beings.
It’s crazy the sheer amount of work I can get done on my phone now because of LRMs.
I’m really happy about this because I like to move around, pace etc.
I'm wondering how much of this "AI risk" stuff is just human nature. Like the moment an alien intelligence exists we fear it and assume it's a threat. No one is basing their fear on actual measured dangers. It's all vibes rn because there's nothing to measure.