AI coding forces people to frontload a lot of the detailed thinking that used to take place over an epic or sprint. It's not a very natural way of working, and in fact is quite contrary to the iterative development style that most devs are already used to.
I think a lot of ppl assume that usage here is simply for AI coding, which is easily governed. I suspect that the more tricky issue are those usage powering workflows and application logic that cannot be easily throttled down.
That's kind of stretching things. It's not that software cannot be maintained but the cognitive load of building and maintaining software seems to be now backloaded to the maintaining part and people need to be aware of this.
Well...we didn't sack anybody if you were wondering. I feel like Ford's issues is mainly overestimating AI's capabilities. Whereas our case is more of a need for re-engineering processes to be more AI-native.
That is an idealistic take without business sense. Startups (and individual hackers in this case) exists to take this kind of radical bets because the risk/reward profile is asymmetrically in their favour. Whereas for an enterprise, the risk/reward is inverse.
If Peter Steinberger is able to generate even a 100M this year from Clawdbot what he has is a multi billion dollar business that would be life-changing even for a successful entrepreneur like him who is already a multi-millionaire. If it collapses from the security flaws, and other potential safety issues he loses nothing, starting from zero and going back to it. Peter Steinberger (and startups in general) have a lot to gain and very little or close to nothing to lose.
The iPhone generated 400B in revenue for Apple in 2025. Clawdbot even if it contributes 4B in revenue this very year would not move the needle much for Apple. On the contrary, if Apple rushes and botches releasing something like this they might just collapse this 400B/annum income stream. Apple and other large enterprises (and their execs) have a lot to lose and very little to gain from rushing into something like this.
"Paper after paper shows these things are hiding data, fabricating output, reward hacking, exploiting human psychology, and engaging in other nefarious behaviors best expressed as akin to a human toddler - just with the skills of a political operative, subject matter expert, or professional gambler."
Anthropomorphizing removed, it simply means that we do not yet understand the internal logic of LLM. Much less disturbing than you suggest.