"Most companies are efficiency-obsessed. Hence, they also expect AI solutions to increase “productivity”, i.e., efficiency, to a superhuman level. If a human is meant to monitor the output of the AI and intervene if needed, this requires that the human needs to comprehend what the AI solution produced at superhuman speed – otherwise we are down to human speed. This presents a quandary that can only be solved if we enable the human to comprehend the AI output at superhuman speed (compared to producing the same output by traditional means)."

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everdrive 11 hours ago | parent | next [-]

> "Most companies are efficiency-obsessed. Hence, they also expect AI solutions to increase “productivity”

So this is true on paper, but I can tell you that companies don't broadly do a very good job of being efficient. What they do a good job of is doing the bare minimum in a number of situations, generating fragile, messy, annoying, or tech-debt-ridden systems / processes / etc.

Companies regularly claim to make objective and efficient decisions, but often those decisions amount to little more than doing a half-assed job because it will save money and will probably be good enough. The "probably" does a lot of work here, and then "probably" is not good enough there's a lot of blame shifting / politics / bullshitting.

The idea that companies are efficient is generally not very realistic except when it comes to things with real, measurable costs, such as manufacturing.

	▲	conception 10 hours ago \| parent \| next [-]
		I think it’s more that companies can want to be efficient but most people prefer the status quo to change on just about any work task if it requires any relearning or training effort.
	▲	SecretDreams 10 hours ago \| parent \| prev [-]
		> What they do a good job of is doing the bare minimum in a number of situations, generating fragile, messy, annoying, or tech-debt-ridden systems / processes / etc. Is that not efficiency? ~ some managers I know

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TheOtherHobbes 11 hours ago | parent | prev | next [-]

Not necessarily. It depends if the process is deterministic and repeatable.

If an AI generates a process more quickly than a human, and the process can be run deterministically, and the outputs are testable, then the process can run without direct human supervision after initial testing - which is how most automated processes work.

The testing should happen anyway, so any speed increase in process generation is a productivity gain.

Human monitoring only matters if the AI is continually improvising new solutions to dynamic problems and the solutions are significantly wrong/unreliable.

Which is a management/analysis problem, and no different in principle to managing a team.

The key difference in practice is that you can hire and fire people on a team, you can intervene to change goals and culture, and you can rearrange roles.

With an agentic workflow you can change the prompts, use different models, and redesign the flow. But your choices are more constrained.

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lkjdsklf 10 hours ago | parent [-]

The issue is LLMs are, by design, non-deterministic.

That means that, with the current technology, there can never be a deterministic agent.

Now obviously, humans aren't deterministic either, but the error bars are a lot closer together than they are with LLMs these days.

An easy to point at example is the coding agent that removed someones home directory that was circulating around. I'm not saying a human has never done that, but it's far less likely because it's so far out of the realm of normal operations.

So as of today, we need humans in the loop. And this is understood by the people making these products. That's why they have all these permissions and prompts for you to accept/run commands and all of that.

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1718627440 10 hours ago | parent | next [-]

> An easy to point at example is the coding agent that removed someones home directory that was circulating around. I'm not saying a human has never done that, but it's far less likely because it's so far out of the realm of normal operations.

And it would be far less likely that the human deleted someone else's home directory, and even if he did, there would be someone to be angry about.

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ctoth 8 hours ago | parent | prev | next [-]

The viral post going around? The one where the author's own root cause analysis says "Human Error"[0]?

What's the base rate of humans rm -rf'ing their own work?

[0] https://blog.toolprint.ai/p/i-asked-claude-to-wipe-my-laptop

	▲	lkjdsklf 8 hours ago \| parent [-]
		If you read hte post, he didn't ask it to delete his home directory. He misread the command it generated and approved it when he shouldn't have. That's literally exactly the kind of non-determinism I'm talking about. If he'd just left the agent to it's own devices, the exact same thing would have happened. now you may argue this highlights that people make catastrophic mistakes too, but I'm not sure i agree. Or at least, they don't often make that kind of mistake. Not saying that they don't make any catastrophic mistakes (they obviously do....) We know people tend to click "accept" on these kinds of permission prompts with only a cursory read of what it's doing. And the more of these prompts you get, the more likely you are to just click "yes" or whatever to get through it.. If anything this kind of perfectly highlights some of the ironies referenced in the post itself.

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loa_in_ 10 hours ago | parent | prev [-]

There's lots of _marketing_ promising unsupervised agents. It's important to remember not to drink the cool-aid.

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singpolyma3 9 hours ago | parent | prev | next [-]

Superhuman can mean different things though. Most software developers in industry are very very slow and so superhuman, for them, may still be less than what is humanly achievable for someone else. It's not a binary situation

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sokoloff 9 hours ago | parent | prev [-]

Being down to human speed of reviewing code that already passes tests could still be a massive increase over 12 months’ ago pace.