Ethan Mollick

You should read the details.

The Shape of the Thing Where we are right now, and what likely happens next

I wrote about the exponential improvement path of AI, the early signs of massive transformations in the nature of work (including software companies where nobody codes any more), and how one week in February was an omen of our future as things get weirder. open.substack.com/pub/oneusefu...

I had Codex create a version of the map of the lighthouses of the Northern seas, including real colors, light patterns & distances

But then I had it also create a mode set in a Lovecraftian 1920s where you need to place lighthouses to ward off things from the Deep: night-watch-bulwark.netlify.app

(And, of course, there is no sign that AI development is stopping right now).

I don't feel like this fact has been fully absorbed yet, and a lot depends on companies and individuals making decisions now about how we can use AI to make white collar work better for both workers and organizations, rather than taking the path of pure automation.

It is very clear that we could stop AI development right now and it would still transform a substantial portion of white collar work, often unrecognizably, over the next 5-10 years as people figure out how to make the technology work in various industries, even given current models' limitations.

oh, sure, its on my github - will post when back at computer if you cant find it

I like how "happy" Claude was with what it made when it did its own initial quality check

This is why we still need humans!

Here are all the lighthouses of the Northern Seas, each light is the right color, each turns or pulses at the right frequency, and is scaled with its brightness. You can also see how far they are visible.

I had Claude Code build this by giving instructions in English: lighthouse-atlas.netlify.app

Here is a full implementation of the Chinese Room using a printed copy of GPT-1 in case you have a few spare years and want to actually run the thought experiment for real, for some reason. You can also download 80 volumes of GPT-1 weights for free to do it: weights-press.netlify.app/pdfs/The-Chi...

Hearing some doubts about whether this is a truthful report, so deleting, but the point about agents remains true!

-Gemini 3.1 Pro is closest, but the ice is a little obvious, and it completely flubs the explanation about why the ice thing was important.

-Claude forgets to add the actual clue to the puzzle (and the details are too obscure), a classic planning problem for LLMs.

-ChatGPT 5.4 Pro creates a completely obvious clue and then proceeds to write with the over-elaborate metaphors and complications that have haunted ChatGPT fiction....

Probably

Another unsolved (& admittedly hard for humans, too) AI benchmark: "write a satisfying 10 paragraph murder mystery. the pieces you need to solve the mystery should be clear enough in the first five paragraphs that you could solve it, but obscure enough that the vast majority of people will not"

To be clear, we also don't know that much about deeper alignment of AIs either.

Paper (found by Alexander Long): arxiv.org/pdf/2512.24873

Skills are among the most consequential new tools for AI, and Anthropic just released a very impressive nontechnical Cowork Skill that builds Skills, including doing interviews & providing benchmarks through parallel tests

I think you still need to add the human touch but this is a big leap forward

To clarify: Gemini Deep Think is a really smart model, but it doesn't have access to the same tools as Claude or ChatGPT - it can't download files, cannot consistently run code on its own, cannot produce downloadable files, does not clearly show when it does web search, etc

GPT-5.4 Pro, Opus, and Gemini DeepThink: "Prove to me in a PowerPoint that there was no advanced dinosaur civilization by downloading whatever data you think appropriate & running tests"

GPT-5.4 and Claude downloaded data and did some original analyses, but someone build a harness for Deep Think!

Economist Alex Imas has been tracking the evidence on AI and productivity changes, and now thinks that the macro-economic data is, rather suddenly, showing the increase in productivity that we have been seeing in our micro research. aleximas.substack.com/p/what-is-th...

Had early access to GPT-5.4 and Pro. The stats are very good and so are the models.

One fun illustration of progress, this is the prompt "the book Piranesi as a p5js 3d space. do it for me," back in 2024 in GPT-4 (which took multiple corrections) and in GPT-5.4 Pro, which did it in one prompt.

It is one of the weirdest divides, I speak to two companies in the exact same industry and one has been using AI for the past 18 months and the other has a committee that has to approve every use case individually and talk about how AI companies will train on their data.

It is amazing how many companies I talk to STILL have AI effectively blocked by IT & legal departments for out-of-date reasons when many companies in regulated industries have figured out ways to deploy enterprise ChatGPT, Claude & Gemini (including CLIs like Code) without any apparent problem.

Content before 2022 is the Roman shipwreck lead or the Scapa Flow steel of human information, anything afterwards could be influenced by AI: directly written by AI, as a result of co-work with AIs, or just as a result of ambient contamination as AI style slips unconsciously into our work.

There was a two year long steady growth period from GPT-4 to the next big leap of o3, where the other labs caught up with GPT-4 and released some really good models along the way (New Sonnet among them). Also o3 should have been named GPT-5

From an AI user perspective, the four big leaps so far in ability:
1. GPT-3.5 (ChatGPT, November 2022)
2. GPT-4 (Spring 2023)
3. Reasoners (starts with o1-preview, but the real deal was o3, Spring 2025)
4. Workable agentic systems (Harness + good reasoner models, December 2025)

I suspect that the other labs will have a Cowork competitor sooner rather than later (though whether they will have good Excel and Powerpoint agents soon is less clear). Deep Think might be as capable as GPT 5.2 Pro but is missing the harness and UX to actually use that power.

Stuff that individual labs have to which there is no equivalent product from the others:
-Claude Cowork is the only non-technical local agent
-NotebookLM is the only information-focused app
-GPT-5.2 Pro is the only harnessed deep thinking model capable of very hard problems