Aaron Levie (@levie) / X

We’re moving from an era of AI where the output comes roughly at the rate that you can chat back and forth with the AI to work with you, to a period where you can set a problem for a set of agents to go off and do an arbitrarily large amount of work for you. This means

Greg Brockman

@gdb

20h

frontier models, with lots of test time compute, are becoming the engine of scientific discovery

A good lesson in AI is that you need to check back in on the latest with every 3 to 6 months to try something that wasn’t possible before and see if it works again. At no point in AI’s history is that more true than today. Just the past six months of model progress around

This sounds extreme and I wouldn’t have believed it even a year ago, but we’re starting to see plenty of examples of productivity gains that are an order of magnitude or two above output levels pre-AI. With the right harness, a deep understanding of your domain of what you want

Theo - t3.gg

@theo

Nov 6

The gap between an average engineer and the best engineers was never quite 10x, but it was meaningful. AI has made the gap at least 100x.

The interesting thing about AI agents is that as a theoretical matter, their inference can kind of run anywhere. AI is one of the few areas of technology that isn’t *as* sensitive to latency back to the user. Long running agents are now going to be the norm, which means it’s ok

Sara Eisen

@SaraEisen

Nov 5

Be careful what you wish for, America… “The rest of the world is ready and willing” to build data centers - ARM CEO

The future is files. And GPUs.

Fireside Alpha

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Aaron Levie

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