getnormality

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Comment · 1 month ago

I feel you. We take a risk when we check our work less and we own the consequences. That's not new, and it doesn't make us bad. It's just the human condition from time immemorial. The solution is not obsessively combing through every detail of our work, it's better monitoring and control on the places where mistakes can have an impact.

Comment · 1 month ago

Congratulations. You are one of those leading the way, showing how we will adapt and how the world will get better from AI.

Comment · 1 month ago

I gotta hand it to programmers (or whatever we call ourselves now) for sticking to principle on something this trivial.

It was either this or Claude had to become a generic term like sheetrock.

Comment · 1 month ago

I think upweighting the live components of academia is inevitable in the age of automatically produced writing, but I also find it depressing that people think so little of writing that they imagine it obsolete because of AI.

AI writing is aggressively, aggressively mediocre. It is only good for how cheap it is. If you're indifferent to how much better good human writing is than AI writing, you should not be the one to evaluate human writing.

Comment · 1 month ago

> the problem may be less about knowing a particular technique and more about the agent’s ability to keep its actual goal as the primary constraint.

I think the limiting factor is often the human's ability to articulate the goal and hold the agent accountable.

The working memory of technical people and the way they communicate often seems to prioritize how they're doing a task and not why they're doing it. So when they talk to you about their problem, they give you the human equivalent of modem noises and stack traces. This is such a common problem on tech support and Q&A forums like StackOverflow that it spawned its own terminology and website: https://xyproblem.info/

The agents don't respond to XY problems any better than a colleague does, and usually much worse.

An effective colleague asks why, and we need a similar relationship between the agent and its human supervisor.

Comment · 1 month ago

> Makes sense. The kids can see that education isn't really going to be a sellable skill when AI ends up coming into full force.

If true, this is a disastrously foolish thing to believe. Education is only going to become more important as supervising increasingly advanced AI agents becomes more difficult. We need people who understand all different domains of human endeavor at the deepest level possible.

I mean, what's the alternative? AI does everything for me and I play Fortnite all day? Might as well plug yourself into the Matrix.

Comment · 1 month ago

Strong resonance with the famous essay "The Rise of Worse is Better" [1], which contrasted the (better) "MIT/Stanford style of design" with the (worse) "New Jersey approach".

MIT/Stanford:

> Simplicity -- the design must be simple, both in implementation and interface. It is more important for the interface to be simple than the implementation.

New Jersey:

> Simplicity -- the design must be simple, both in implementation and interface. It is more important for the implementation to be simple than the interface. Simplicity is the most important consideration in a design.

TFA maps "simplicity" to "MIT/Stanford simplicity" (simplicity for the user) and "smallness" to "New Jersey simplicity" (simplicity for the developer).

I wonder if the root of the tension between the two schools comes down to the ambiguity of the user/developer distinction. Developers are also users. Simplicity of implementation is helpful to developers when they are working directly on implementation, while simplicity of interface is helpful to developers when they are using other developers' work.