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Not everyone is using AI for everything

gabrielweinberg.com

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Re: Not everyone is using AI for everything

#151
post #82

Earlier quoted context omitted.

> It's tough to answer because you want to hedge for both an AI enthused employer and an AI hesitant employer with limited information about who they are and how they personally use these products. Have you considered just answering truthfully? Would you even want to work somewhere where you need to play a role and where they flip out when you say the wrong word you should've correctly guessed through mind reading? T…

I assume it's because he is seeking to pay rent, food bills, and other expenses through employment.

“I assume it's because he is seeking to pay rent, food bills, and other expenses through employment.”

Fair enough, so if there were one “right” answer, that would be the one to give whether true or not.

But here there is no obvious right answer. If the employer is looking for a particular answer, the poster doesn’t know what it is. In that case, the best thing to say is simply the truth, particularly when the truth that the poster gives here is completely reasonable.

Re: Not everyone is using AI for everything

#152

Earlier quoted context omitted.

I assume it's because he is seeking to pay rent, food bills, and other expenses through employment.

I think honesty is still probably correct - if you're struggling to figure out how to hedge. I think you'd rather have good odds at some companies and 0% at others, rather than abysmal but non-zero odds at all companies. And as an added bonus, you might get hired at a company where you're actually a good fit, rather than one you weasled your way into, and get to pay rent, food bills, and other expenses through employ…

It's pretty easy as an interviewer to spot when a candidate is hedging on a question, and it's the kind of thing that might get discussed in the post-interview debrief.

"Wouldn't give a straight answer on question X" isn't an instant no-hire, but it's not a positive signal.

Re: Not everyone is using AI for everything

#153
post #82
post #72

On the post-grad job hunt right now - I note that most employers will ask in a technical interview or whiteboard interview "how are you using LLMs?" It's tough to answer because you want to hedge for both an AI enthused employer and an AI hesitant employer with limited information about who they are and how they personally use these products. I've been responding with a sort of long winded answer about how 'there is…

> It's tough to answer because you want to hedge for both an AI enthused employer and an AI hesitant employer with limited information about who they are and how they personally use these products. Have you considered just answering truthfully? Would you even want to work somewhere where you need to play a role and where they flip out when you say the wrong word you should've correctly guessed through mind reading? T…

Would being truthful improve my chances of being hired?

Re: Not everyone is using AI for everything

#155

I understand the point being made, but it does feel a bit like writing a post in the early days of the internet saying: "No, everyone is not using the internet for everything." Which would have been entirely true when written, and entirely false a relatively short time later. Everyone does use the internet for everything today, and everyone will use AI for everything soon.

You'll find it hard to pin down what you mean by "everything" otherwise you wouldn't have said that. Nobody uses the internet for everything. Local models are highly likely to dominate in the long run as "good enough" inevitably becomes trivially cheap. This is a very different pattern of incentives and adoption compared to the internet. I think it's more similar to the advent of personal computers. They had a brief…

It seems fair to leave the definition of "everything" to a reasonable person's interpretation. It's obvious that the internet is beyond ubiquitous in modern life.

I agree that where models run will will change over time, probably they'll run everywhere, but it's still the same kind of AI we are talking about.

Smartphones are personal computers.

Re: Not everyone is using AI for everything

#156

> AI has gotten so good that despite any misgivings, “everyone is using A.I.” In my experience, it's a mixed bag. I wrote this comment[0], yesterday. It reflects my current work, and how I am integrating an LLM. I have used it for two parts of my project: 1) The backend (PHP), and 2) The frontend (Swift) It has been a huge help, in both, but #2 is a cautionary tale. It really needs adult supervision, in developing na…

Well Apple just released a bunch of Agent Skills. I tried it on my macOS apps and I noticed some improvements codewise and updated some deprecations I didn’t know existed in Swift.

Re: Not everyone is using AI for everything

#157
post #90

Earlier quoted context omitted.

The typing was never the bottleneck.

Can you type a hundred lines a second? If not, then it is. Code is obscenely low level.

> Can you type a hundred lines a second? If not, then it is.

No one has ever needed to do that for something that is new. And if it’s not new, you want to do it repeatedly with some guarantee of reliability. Not just in an uncontrolled manner.

That is why we have snippet systems, macros and code generators. And the best with code is to solve problem once and reuse the solution. Which we have done with libraries, frameworks and supporting software.

Re: Not everyone is using AI for everything

#158

I've noticed several companies replacing deterministic systems in their support flows with a LLM version that is slower and worse. Many interfaces simply aren't better with AI added

I am seeing similar things in just regular tooling and development. Things that can be solved deterministically or what would have been a simple CLI 5 years ago are now an LLM integration.

Instead of using the LLM to create deterministic tools, we are using LLMs to replace them. It's completely backwards and I don't know why people (especially high ranking people in my company at least) seem to think that this is the way forward. No, I don't want a whole CI pipeline that is just LLM prompts. Yes it's very easy, but it's expensive, slow and prone to failure in ways you can't even predict.

Same things like using LLMs for the code review process. What would have been a simple linting rule is now a pass with an LLM rather than using the LLM to create the linting rule, which it is absolutely excellent at creating.

Re: Not everyone is using AI for everything

#159
post #41

I've noticed several companies replacing deterministic systems in their support flows with a LLM version that is slower and worse. Many interfaces simply aren't better with AI added

That's the completely opposite of what people should do. The laborious task of programing logical work flows is the only reason AI is useful for me.

When I hear about engineers who are bored with coding, I have to imagine it's because the task of "programming logical work flows" has become rote to them.

Instead of refining their approach, or challenging their current knowledge base for discovery of inefficiencies or baseless assumptions, they'd rather hit an "easy" button.

I understand the desire to NOT do work. I understand the desire to spend quality time and free time with family. And I understand the idea that familiarity breeds contempt.

What I don't understand is the willingness to replace a deterministic language/framework/approach with a probabilistic slop machine.

Re: Not everyone is using AI for everything

#160
post #152

Earlier quoted context omitted.

I think honesty is still probably correct - if you're struggling to figure out how to hedge. I think you'd rather have good odds at some companies and 0% at others, rather than abysmal but non-zero odds at all companies. And as an added bonus, you might get hired at a company where you're actually a good fit, rather than one you weasled your way into, and get to pay rent, food bills, and other expenses through employ…

It's pretty easy as an interviewer to spot when a candidate is hedging on a question, and it's the kind of thing that might get discussed in the post-interview debrief. "Wouldn't give a straight answer on question X" isn't an instant no-hire, but it's not a positive signal.

ironically, I'd understand people not giving a straight answer on this particular topic
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