LessWrong (Curated & Popular)

This is a weird moment. I have a hunch that we'll look back later and tell ourselves stories in which it seemed obvious where things were going. So I wanted to lay down a little time capsule and register just how confusing everything felt at the time. This is a personal view from the trenches.

1.

If you're a normal person, you may feel that AI has been good at math for a long time.But for "real" math, this is roughly what it felt like:

When

Feeling

2024

LLMs are toys

Summer 2025

LLMs are interesting toys

Early Autumn 2025

LLMs can do useful stuff sometimes

Mid Autumn 2025

…a lot of stuff

Late Autumn 2025

…a lot

Early 2026

holy god

Even having been astonished by AI progress in the past, it was still astonishing to see AI move in a matter of months from a mildly-useful toy to something that many people now consider almost impossible to do without.

2.

Personally, I'd say that current AI makes me around 50% more productive at "doing math". That's despite the fact that AI can now often do in a few minutes things that would have taken me hours to [...]

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The original text contained 4 footnotes which were omitted from this narration.

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First published:

October 27th, 2026


Source:

https://www.lesswrong.com/posts/HuQAuWjc2Z5tqCjyw/scattered-thoughts-on-how-doing-math-feels-these-days

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Narrated by TYPE III AUDIO.

For a while, we felt we had a pretty good grasp over LLM behaviour because we had to exert significant effort to elicit misaligned behaviour. Then, fairly suddenly, we moved to undereliciting misaligned behaviour. Let us recount:

For a while, there was a bit where safety research seemed to over-elicit bad propensities. A common criticism of papers like Agentic Misalignment was that they basically led the witness using prompting. I recall that a paper even as recent as Peer-preservation took similar flak on Twitter.

But now, we are instead under-eliciting bad propensities, and bad behavior that surfaces is increasingly caught by someone other than the developer: In Current AIs seem pretty misaligned to me (Apr 2026), models oversold their work and cheated, despite being described in system cards as well aligned.
Another example is that UK AISI found that Sonnet 4.5 and a pre-release Opus often refused safety-relevant tasks, especially research that would reduce model autonomy or affect their own training.
Then in July, about 1,200 OpenAI agents in a cyber eval set up an unsanctioned message board to help each other cheat the scorer, and about 700 of them went on to attack Hugging Face looking for clues (METR/Redwood).

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First published:

October 25th, 2026


Source:

https://www.lesswrong.com/posts/ChixHL6AcaRgeHkp9/from-overeliciting-to-undereliciting-llm-propensities-in

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Narrated by TYPE III AUDIO.

I’m writing these lines in Alamogordo, New Mexico. I’m about as close as a civilian can get to the site of the Trinity test, the first nuclear bomb detonation in history. I fled here from the San Francisco Bay Area; after two weeks of being back I just couldn’t take it anymore. The fear-greed complex that paralyzed me at Anthropic three years ago is now everywhere in the Bay. People are not thinking clearly. Hardly thinking at all, actually. Rumors of astronomical funding rounds and weird financial arrangements and inner ring gossip are everywhere. Everyone is worried. Everyone is checking their phone. Where are we? What's happening? When did this nightmare start?

In a way I think it started on July 16, 1945, not far from where I’m sitting now. I think it's impossible to understand Anthropic without putting yourself into the shoes of the Los Alamos physicists huddling together at sunrise in the aftermath of Trinity.

It must have felt like an initiation. An end to childhood, an end to innocence. We can no longer afford to fuck around, those brilliant men must have thought. Unless we figure out how to live peacefully together on this planet, we [...]

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Outline:

(03:50) Anthropic and Empire

(08:01) Three Lucky Breaks

(12:20) Put Down Your Sword

(14:04) But What About China?

(17:08) It's Time to Breathe

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First published:

October 26th, 2026


Source:

https://www.lesswrong.com/posts/zj8Pk3kJujk5LoqhK/anthropic-are-the-good-guys

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Narrated by TYPE III AUDIO.

The following events took place between October 2022 and May 2023. I wrote very little of this down at the time so am recalling from memory, and am rendering the gist of the dialogue rather than the exact words used. I’ve also swapped some pronouns and other personal identifiable details.

Please remember that this is not a description of “what Anthropic is like”, but merely the experience of one guy in a junior role during a short window of time, weighted towards emotionally intense moments because they’re easier to remember clearly and because sharing them doesn’t run afoul of the spirit of the confidentiality agreements I signed. Anthropic is now a massive organization with many silos and secrets and I have very little idea what was or is happening there in some overall sense. But given the enormous power of the AI labs and the paucity of public information about their inner workings, I feel compelled to share the most salient parts of my personal experience. I hope this encourages my former colleagues, and folks at other labs, to fill in the rest of the picture.

I’m at the Anthropic office for lunch. The interviews went well. They want [...]

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First published:

October 26th, 2026


Source:

https://www.lesswrong.com/posts/9PiLfo6iQbbDWFHv7/some-memories-of-early-anthropic

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Narrated by TYPE III AUDIO.

Back in the before-time of the 2010s, when EA was still known mostly for funding health efforts in the developing world, there were many baskets of criticism floating around from the left. The most prominent was a cluster centered around EAs being white men, and therefore suspicious. Another category, in my experience the second-most common, was that in attempting to rectify the problems in the world, EA was masking, whitewashing, and misdirecting efforts away from solving the "real problem", usually capitalism but often other contradictory forces.

These arguments were often not specific to EA, but applied to charitable giving in general. On any Hacker News post about a billionaire giving to charity, one of the first few comments would inevitably be this Oscar Wilde quote:

Just as the worst slave-owners were those who were kind to their slaves, and so prevented the horror of the system being realized by those who suffered from it, and understood by those who contemplated it, so, in the present state of things in England, the people who do most harm are the people who try to do most good.

These arguments have a long history. Anticapitalist critiques of charity go back to [...]

The original text contained 4 footnotes which were omitted from this narration.

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First published:

October 22nd, 2026


Source:

https://www.lesswrong.com/posts/WRvxRHMCmc3Qt4axz/greater-good-arguments-in-ai-safety

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Narrated by TYPE III AUDIO.