The reason companies, or at least sales and marketing, are so incredibly after AI is that it can raise response rates on spam, and on ads, by "Hyper-personalizing" them by actually reading the social media accounts of the people looking at the ads and making ads directly based on that.

Same. I interface with a team who refuses to conduct business in anything other than Excel, and because of dated corporate mindshare, their management sees them more as wizards instead of the odd ones out.

"They're on top of it! They always email me the new file when they make changes and approve my access requests quickly."

There are limits to my stubbornness, and my first use of LLMs for coding assistance was to ask for help figuring out how to Excel, after a mere three decades of avoidance.

After engaging and learning more about their challenges, it turned out one of their "data feeds" was actually them manually copy/pasting into a web form with a broken batch import that they'd give up on submitting project requests for, which I quietly fixed so they got to retain their turnaround while they planned some other changes.

Ultimately nothing grand, but I would never have bothered if I'd had to wade through the usual sort of learning resources available or ask another person. Being able to transfer and translate higher level literacy, though, is right up my alley.

I’ve had similar experiences where AI saved me a ton of time when I knew what I wanted and understood the language or library well enough to review but poorly enough that I’d gave been slow writing it because I’d have spent a lot of time looking things up.

I’ve also had experiences where I started out well but the AI got confused, hallucinated, or otherwise got stuck. At least for me those cases have turned pathological because it always _feels_ like just one or two more tweaks to the prompt, a little cleanup, and you’ll be done, but you can end up far down that path before you realize that you need to step back and either write the thing yourself or, at the very least, be methodical enough with the AI that you can get it to help you debug the issue.

The latter case happens maybe 20% of the time for me, but the cost is high enough that it erases most of the time savings I’ve seen in the happy path scenario.

It’s theoretically easy to avoid by just being more thoughtful and active as a reviewer, but that reduces the efficiency gain in the happy path. More importantly, I think it’s hard to do for the same reason partially self driving cars are dangerous: humans are bad at paying attention well in “mostly safe and boring, occasionally disastrous” type settings.

My guess is that in the end we’ll see less of the problematic cases. In part because AI improves, and in part because we’ll develop better intuition for when we’ve stepped onto the unproductive path. I think a lot of it too will also be that we adopt ways of working that minimize the pathological “lost all day to weird LLM issues” problems by trying to keep humans in the loop more deeply engaged. That will necessarily also reduce the maximum size of the wins we get, but we’ll come away with a net positive gain in productivity.

That's a dangerous game to play with Bash, I'm not sure if there's another language more loaded with footguns than that.

Agreed. I think that many companies force people to use AI in hopes that somebody will stumble upon a killer use case. They don't want competitors to get there first.

> but they probably see the state of the art advancing quickly so that companies who take a wait-and-see approach will be late to the game when AI is a substantial productivity enhancer.

This makes no sense for coding subscriptions. Just how far behind can you be in skills by taking a wait and see position?

After all, it's not like this specific product needs more than a single day for the user to get up to speed.

It's incomplete but not false universally. Politics is part of how businesses work. Many companies which adopted AI now expected results now. People who promised results now have reputations on the line. Incentives influence beliefs.

> Note they may even believe that today's AI systems may not be much of a net benefit, but they probably see the state of the art advancing quickly so that companies who take a wait-and-see approach will be late to the game when AI is a substantial productivity enhancer.

This doesn't make a huge amount of sense, because the stuff is changing so quickly anyway. It's far from clear that, in the hypothetical future where this stuff is net-useful in five years, experience with _today's_ tools will be of any real use at all.

> The main reason for the push from the top is probably because they believe companies that don't adopt AI strategies now and ensure their programmers are familiar with AI toolsets will be at a competitive disadvantage. Note they may even believe that today's AI systems may not be much of a net benefit, but they probably see the state of the art advancing quickly so that companies who take a wait-and-see approach will be late to the game when AI is a substantial productivity enhancer.

Yes, this is the correct answer.

Companies do not necessarily understand sunk cost fallacy.

> ensure their programmers are familiar with AI toolsets will be at a competitive disadvantage

But more importantly, this is completely inconsistent with how banks approach any other programming tool or how they approach lifelong learning. They are 100% comfortable with people not learning on the job in just about any other situation.

> this is definitely not it.

> is probably because

I don't mean to be contrary, but these statements stand in opposition, so I'm not sure why you are so confidently weighing in on this.

Also, while I'm sure you've "been in senior engineering management", it doesn't seem like you've been in an organization that doesn't do engineering as it's product offering. I think this article is addressing the 99% of companies that have some amount of engineers, but does not do engineering. That is to say: "My company does shoes. My senior leadership knows how to do shoes. I don't care about my engineering prowess, we do shoes. If someone says I can spend less on the thing that isn't my business (engineering) then yes, I want to do that."

[dead]

Do you have any data to backup the claim: “vast majority of companies understand suck cost fallacy.”

I’m assuming you meant “sunk” not “suck”. Not familiar with the suck fallacy.

Can you buy a subscription and see if it benefits you ?

> The 95% isn't a knock on the AI tools, but that enterprises are bad at integration.

You could read this quote this way. But the report knocked the most common tools.

The primary factor keeping organizations on the wrong side of the GenAI Divide is the learning gap, tools that don't learn, integrate poorly, or match workflows. Users prefer ChatGPT for simple tasks, but abandon it for mission-critical work due to its lack of memory. What's missing is systems that adapt, remember, and evolve, capabilities that define the difference between the two sides of the divide.[1]

[1] https://mlq.ai/media/quarterly_decks/v0.1_State_of_AI_in_Bus...

Have to pay the power bill for the data centers for GAI. Might not be profitable.

Doubt the form has anything to do with how "controversial" it is. NANDA is using the paper's popularity to collect marketing data.

Fun fact, it was always behind a form if you wanted to access it through the original/primary link.

(You're responding to an LLM-generated comment, btw.)

No doubt in ten years chatgpt will mostly be telling you things it was paid to say.

The saddest part is we used to have highly functional search engines two decades ago, where you would results from subject matter experts.

Today it’s only the same SEO formatted crap without answer.

I am working on a solution.

AI is what you tell the board/investors is the reason for layoffs and attrition.

Layoffs and attrition happen for reasons that are not positive, AI provides a positive spin.

> No employee is resigning when an employer tells the employee they are terminated due to AI replacing them.

No, but some are resigning when they're told their bonus is being cut because they didn't use enough AI.

Using AI makes me want to resign from life, it removes all the fun and joy from coding.

I absolutely will resign if my job becomes 100% generating and reviewing AI generated slop, having to review my coworker's AI slop has already made my job way less fun.

Eh, I have plenty of "bullshit work". Only that, actually, for the foreseeable future.

Building clusters six servers at a time... that last the order of weeks, appeasing "stakeholders" that are closer to steaks.

Whole lot of empty movement and minds behind these 'investments'. FTE that amounts to contracted, disposed, labor to support The Hype.

That's exactly it is! Thank you!

Trial and error?

I mean I'm in a similar situation in that I'm a games developer and no AI system has been trained on the details of PS5/Xbox/Switch development since those are heavily NDA'd and not available to the public. So I learn by reading docs which are available to me as a registered developer, but AI doesn't have that ability and it hasn't been trained on this.

It's not inconsistent to say there's a financial bubble and also genuinely think it's a new era for software development.

There aren't enough programmers to justify the valuations and capex

Dot com was a financial bubble, but the internet was still very usefull. Financial markets can become (often are) dislocated from reality.

I sometimes use grok. But not much. Your confusion is strange. I never said the tech is a bubble(it can be used today, although in very limited manner, compared to how it is being sold to the public), just the financial aspect of it. If you'd be more educated in investing, economics or geopolitics you'd understand what is going on. I am not being hyperbolic here. Even Altman admitted AI is a bubble. It's really no secret to anyone. But bubbles will be ridden no matter what, all the way up, until they pop. So knowing it is a bubble does not change much. We just know what we can expect once it pops.

tl;dr I was merely answering the question the article proposes.

> AI is useful to people who read and understand the answers and who would have eventually come up with a similar result on their own.

I am such a one, and AI isn't useful to me. The answers it gives me are routinely so bad, I can just answer my own questions with a search engine or product documentation faster than I can get the AI to give me something. Often enough I can never get the AI to give me something useful. The current products are shockingly bad relative to the level of hype being thrown about.

It also happens when you ask it to do simple things like create comments. At least 400 words and still it will regurgitate/synthesize, often with a "!", the content you're asking it to comment on.