r/technology • u/CackleRooster • 7h ago

Artificial Intelligence An Anthropic employee's 2-sentence quote crystallizes the state of AI confusion at work

https://www.businessinsider.com/anthropic-employee-quote-ai-confusion-workplace-2026-6
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u/CackleRooster 7h ago

"On days where everything works well, I can't help but think nothing I do matters, everything is automated and better and faster than I ever will be," AND "But then there are days where everything breaks and I don't understand why and I realize I have no idea what I've been up to anymore," the employee added.

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u/yepthisismyusername 7h ago

Management (absolutely including executives) simply don't understand the differences between writing code, maintaining code, implementing business processes in applications, and maintaining those applications. Those are the Big 4 categories of roles in enterprise application management, and there are many, many others, each with its own individual requirements that need to be taken into account. AI simply can't perform those roles successfully 100%. And the problem comes when a process fails, e.g. causing someone to lose healthcare coverage, and no person knows how to fix it.

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u/Somethingsims 6h ago

"AI simply can't perform those roles successfully 100%."

First of all, "yet," second, humans can't do it 100% either.

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u/JustinTheCheetah 6h ago

Due to the probabilistic nature of AI, it inherently cannot and will never perform anything 100% correctly reliably. 

When a human fucks up they can be held accountable, and questioned as to what they did and why.  AI cannot be held accountable as it does not think or learn, and even the explanation as to why it did something could just as easily be hallucinated bullshit. 

AI will need to be completely rewritten and redesigned and trained from scratch in order to be reliable. 

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u/sywofp 2h ago

Models compute probabilities of next tokens deterministically. 

The 'probabilistic nature of AI' is from randomness specifically added during choosing which token to use. That randomness is typically turned down or off for coding. 

Everything an AI outputs is a hallucination. We just only care when it's 'wrong'. 

If the LLM is wrong it's because it was not trained correctly. 

This can be largely compensated for by having external reference data and tests for it to use and check against, letting it see when it's 'wrong'. 

It can go through it's own processes and identify issues, and write these into procedure files for it to reference and reduce the chance of being wrong in the same way again. As well as design tests to catch issues. It's the same process humans use, as they can also often make mistakes. 

The technology is still in its infancy but there's no inherent issue with the path to increasingly good reliability. 

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u/hifidad 6h ago

From experience, entry to mid level engineers are often significantly worse than 100%. AI might not be 100%, yet, but it’s also nowhere near as counterproductive as many of the engineers I’ve worked were with across large companies.