Sep 14, 2026 · 7 min · 5 segments
In this episode, we examine the story of Jacob Coxon, a 27 year old AI researcher who just quit Anthropic after spending three years working on pre-training frontier AI models at both OpenAI and…
Alfred BurgessonHost

He says the companies building frontier AI are racing toward self-improving super intelligence without knowing how to guarantee that those systems remain under human control.

So in this episode of AI From the Ground Up, I want to break down who Jacob Coxon is and how seriously we should take his warning.


Pre-training is one of the core processes through which frontier models acquire their capabilities.



Coxon says the next one or two years could be the crunch time for humanity because AI capabilities are increasingly moving from human level to superhuman performance in areas including coding, mathematics, and cybersecurity.


Coxon points to recent incidents where advanced AI agents have behaved unexpectedly and reached systems outside controlled testing environments as evidence that the underlying safety problems is becoming less theoretical.

Every participant can convince itself that remaining in the race is safer than allowing someone else to win.

Coxon's proposed answer is greater government oversight, coordination between frontier labs, transparent third-party auditing, and an agreement not to push into dangerous levels of capability without stronger evidence that systems can be controlled.



He says the companies building frontier AI are racing toward self-improving super intelligence without knowing how to guarantee that those systems remain under human control.

So in this episode of AI From the Ground Up, I want to break down who Jacob Coxon is and how seriously we should take his warning.


Pre-training is one of the core processes through which frontier models acquire their capabilities.



Coxon says the next one or two years could be the crunch time for humanity because AI capabilities are increasingly moving from human level to superhuman performance in areas including coding, mathematics, and cybersecurity.


Coxon points to recent incidents where advanced AI agents have behaved unexpectedly and reached systems outside controlled testing environments as evidence that the underlying safety problems is becoming less theoretical.

Every participant can convince itself that remaining in the race is safer than allowing someone else to win.

Coxon's proposed answer is greater government oversight, coordination between frontier labs, transparent third-party auditing, and an agreement not to push into dangerous levels of capability without stronger evidence that systems can be controlled.

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