Rob Wiblin

speaker

5,091 appearances 15 recordings 1 series first heard Oct 2021 last heard 6 Aug

Rob Wiblin’s voice in public audio — every appearance, attributed to the second.

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recordings per month · last 12 months

Recordings per month over the last 12 months — 13 in all, peaking in Apr 2026 with 3.

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80,000 Hours Podcast · What the hell happened with AGI timelines in 2026? – Rob Wiblin · 4 Aug 2026 podcast

It wasn't just Andrej Karpathy whose mind was blown by this.

Over December, tens of thousands of other programmers using it through Cloud Code started shouting to anyone willing to listen to them that as far as they could see, AI agents were really good now.

Finally, they could leave Claude to do significant projects on its own without fully expecting it to trip over its own feet in the first five minutes.

And AI Twitter filled up with entire computer games and apps built by Claude over 10 to 20 hours of independent work from a single short prompt.

The arrival of these highly capable AI agents was a big surprise to most people, including me.

After all,

Literally no progress, as far as I can tell, has been made on any of the purported blockers, like continual learning or world models.

And to date, as far as I know, we still haven't gotten a better explanation for what happened than, yet again, scaling and reinforcement learning worked.

We threw more data and more compute at the best models.

And as they got smarter, their chance of screwing up any individual step in a long chain of them fell low enough that it was finally faster to delegate a well-specified task to them than it would be to attempt that task yourself.

Maybe the only surprise, though, was that we were so taken aback by this.

The EPO Capabilities Index is an effort to zoom out and blend together AI performance on 40 benchmarks across a wide range of different domains.

If I had to look at just one number, this is the indicator of frontier progress that I personally care the most about.

The EPO Capabilities Index finds that overall, AI progress was roughly constant from 2022 to 2024.

And then with the arrival of reasoning models in September 2024, it started advancing two to three times faster than before, a trend that continues through the present day.

Over this entire period, people kept predicting AI was about to hit a wall for one reason or another, but it simply never did.

Now, there are other ways of slicing and dicing this data which don't show as large an acceleration.

But on even the most pessimistic reading, during late 2025, AI was advancing as fast as it ever had before.

And on top of that, the companies were super focused on using reinforcement learning from verifiable rewards, or RLVR, to get coding agents to work well.

It was their number one priority.

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