-ish; while you can be fairly certain it reads the docs, whether they’ve been used/synthesized is just about unknowable. The output usually looks great, but it’s up to us to ensure its accuracy; we can make it better in aggregate by tweaking dials and switches. To mitigate this we’re asking AIs to create plans and todo lists first, which adds some rigor but again we can’t know if the lists were comprehensive or even correct. It does seem to make the output better. And if the human doesnt read the docs, they can be beaten!

40 words per minute is equivalent to about 50 tokens a minute.

I just took GPT-5, output is $10 per million tokens. Let's double the cost to account for input tokens which are ($1.25 per million / $0.125 if cached).

For 1 million tokens it would take a 40 wpm typist.. around 20K minutes to output that $20 of worth of text. That is just typing. So about 300 hours of non-stop effort for that $20.

So even if you say.. oh.. the real price is $100 not $20. The value changes are still shattering to the previous economic dynamics.

Then layer in that also as part of that value, the "typist" is also more skilled than the average working person in linguistics, software engineering, etc. Then that value is further magnified.

This is why I say we have only begun to barely see the disruption this will cause. Even if the models don't get better or cheaper, the potential impact is hard to grasp.