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 clearly a learning curve for how this technology fits into any process and how I always always always double double double check yadayadayada'

I'm probably using the chat/ask functionality on a daily basis for quick debugging / new technology learning questions but I have yet to really use the fully agent or computer-use products because I've had more bad results than good the few times I've tried them (re-factoring a big repo of decades old fortran+C code for modern compiler/OS some things started to work but ultimately I abandoned that effort).

It's important to factor in just how many US adults are basically illiterate nowadays.

As of 2023, 27% of American working-age adults were at a PIAAC Literacy Level of 1 or below, out of a total of 5 levels. This has gotten drastically worse in the past 10 years as, in 2013, Level 1 and below was only 17%.

Full scores for 2023 are: % Level 1 or below: 27% Level 2: 29% Level 3: 31% Level 4/5: 13%

For reference, Level 1 means someone can't really handle a full page of text, and can sort of handle simple 1-page web pages. Level 2 is the point where someone can start to handle a few pages of straightforward text, but still nothing particularly complicated.

(Both of those descriptions undersell just how bad it really is, but I'll leave it at that, for the sake of brevity.)

People that aren't using AI at all often aren't using it because they effectively can't. On a fundamental level.

Source: https://nces.ed.gov/surveys/piaac/2023/national_results.asp

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

> 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 native UIKit Swift apps. I'm realizing how truly bad the code it wrote was. I mean, terrible.

That's jarring, because it did a great job with #1. It made sound, reasonable design decisions, and provided code that is better than what I would write.

With #2, it behaved exactly like an inexperienced engineer, panicking, when confronted with real-world problems. My rewrite is going to feature a much simpler, sound approach.

All that said, it has been a net positive, and has increased my productivity by a large margin.

I guess the lesson I needed to get from this, is that it is good at helping me to find problems, but maybe not so good at fixing them.

[0] https://news.ycombinator.com/item?id=48515217

> People are consuming AI like they eat meat: some are embracing it, some are limiting their use of it, and some are avoiding it altogether.

That's an interesting analogy as, despite the real ecological issues with it and principled arguments against meat eating, in general meat consumption has trended upward globally in country after country for decades.

I think the gap is because 1. For coding, Claude is amazing - mainly because of its curated skills and because massive amounts of working code has already been carefully labeled over the last decade or so via GitHub. And because with any Turing complete language, there is only so much one can do.

But 2. For most other things, LLMs are fairly underwhelming. Research is usually mediocre. Try being rigorous and repeat your research prompt many times - then make a confusion matrix to tally up how many false positives and false negatives occur. And for the rest, be honest and ask yourself if the LLM is doing much more than a basic search engine query or trip to Wikipedia would have told you. For “normie” use cases, it’s handy-ish but far from revolutionary

One thing I'd personally like to see a little more discussion of (at least within my social circles) is.. what exactly does "using AI" mean?

How does this connect to everyone's high level ideas/thoughts about "tech", "AI" and "morals and feels" etc. These lines can start to seem a little blurry, at least for me.

For example, would we say my partner is "using AI" (for all intents and purposes), if she's frequently using Google.com throughout the day, and then ends up picking and believing the AI generated answer overview at the top of the SERPs almost every time?

Or do we feel "uses AI", is more along the lines of the vampire kids running 1000 sub-agents on a mattress floor in SF?

I kind of find the whole spectrum really interesting because even basic phone use is now stuffed with AI, whether we choose to label it or not.

I fear AI is going to be used for everything not because it's the best solution, but because people are inherently lazy and just want to get their thing done, and they don't care so much about the quality.

"low effort and convenient" seems to consistently win over "best quality" and this is going to be a downgrade in everything, for everyone

Anyone who does a Google search gets a satisfactory looking answer as the very first entry. I daresay most people don't go beyond that, not even the entries on the first page, let alone go to the next. I argue that this is at the level of everyone for everything.

> More than 30 percent of the US working-age population is using AI [meaning about 70% isn’t], an increase of 3 percentage points from the end of 2025

This makes me less bearish on the AI investments that are being made, if 70% of the working age population isn't using AI then there still is a lot of growth. The future is here, it's just not evenly distributed (yet)

So true, just built a deterministic system to identify duplicated code. It's offline and doesn't use AI on purpose, since a gate that blocks your CI has to give the exact same answer every time, and finding dupes means comparing every function against every other (that's index work). It does NOT use AI. But ironically, I used AI to build it (https://github.com/Rafaelpta/dupehound )

Some of the advantages are second order.

For example; ChatGPT is replacing my Google searching. Not necessarily because it's better, or because it's summaries are better than Google (I find them subjectively better but it's not clear cut).

But because the app has a nice history; can ask a relatively complicated question and go do something else and then come back to it, ask a follow up. Etc.

None of that is specifically an AI benefit, but it's a workflow that really helps, well, flow.

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.

"But they will", "They do, but they don't know", "They do, indirectly"

I don't get these comments.

A counterpoint to this is that we have some real different definitions of AI.

If you consider things like the machine learning filters in your smartphone camera and Google's AI Overviews for searches it's entirely plausible that the US is currently at 75%+ of AI usage.

One of the reasons is that the free options are generally fairly poor and it’s hard to get people to sign up and actually pay for something. Especially if they assume it’s going to be similar quality.

If I worked in marketing/growth for an AI company I would try to consider some ways of breaking through this gap.

Not everyone but most. And I've been having this discussion with people around me a lot lately and everyone that has the ability to think more than half a step ahead sees it(and frankly we are fed up). I previously discussed how a friend admitted that he's never seen the code that powers his project at an S&P 500 company. Yesterday I was talking to another friend and former coworker who complained that when cloudflare went out a month or so ago, his entire team just slammed their laptops and went home cause they couldn't work(no sloppus/sloppenai). Another friend of mine: her dad is in hospital with a terminal disease and her mom (in her late 50's or early 60's, idk) uses chatgpt as a personal therapist. Gatorade-fed crops here we come, Leeerooooy Jeeeenkins!

I only use AI for software development. For writing, I don't use it at all except to translate source materials. So yes, AI is only for software development in my case. The real question is whether I have any value outside of software development. Sometimes I get the feeling that AI is replacing the value I have in society.

True, but you're somehow involved in it even though you don't use AI.

Not to take away from the post, but "everyone is not" should probably be "not everyone is".

Everyone is using AI, issue is not just everyone recognizes what AI actually is, how broadly it's used.

Looking things up and asking questions was always something for a minority of the population so the language model usage being relatively low isn't a surprise.

Problem arises if the non-AI segment is leveraged to create regulations that impact the AI using segment negatively.

everyone might not be using ai. but i see myself reaching for it for every small thing these days. it's like every curiousity or lifestyle choice or optimization is something ai can help research.

i am not saying it's really powerful or great. but the lure is undeniable. because of how low friction it has become.

I'm going back and forth with the llm agents.

They are great on exploring, understanding and finding bugs in existing codebase.

They are great for simple or one time scripts/programs.

They are terrible, really terrible coders. The overengineering is so deep in their training that no matter what is your prompt, your skills or agents.md/claude.md, if you don't babysit them continuously, at some point they will just fuck up your codebase.

Reminds me of this article: https://www.theverge.com/podcast/917029/software-brain-ai-ba...

Software engineers are definitely in a bit of a bubble here. Are we just early adopters who see the value sooner, or does it uniquely benefit software engineering, or do we just like cool automation and we're deluding ourselves that this adds value beyond the cost?

No, everyone is not using AI for everything - yet.

I disagree. Everyone will be using AI for everything, but, increasingly, people won't think about whether they are using "AI" – just like they don't think about using databases.

Nor should they! It's such a shit thing to be emotionally invested in. Imagine people would have been upset about databases. It's really fantastic software and we should be happy to have it, and now go and make the most of it, for all of us.

I am using AI to take on a fun large scale analysis of churches in USA.

I also just bought a completely mechanical film camera to learn a new old skill with no tech to fall back on.

I'm using AI for most things. It has been an incredible improvement to both my quality of life and my wallet. Some of the most high profile items from just the past three months:

- I'm getting my roof replaced due to hail damage. Insurance originally covered only $5k due to depreciation. I fed the insurance policy to AI. I learned about the appraisal clause and invoked it. At the end, I got another $6,500 back.

- I was having issues with plumbing. Four different plumbers came, they all said the cast iron pipes under the house need to change. Quotes ranged from $35k to $55k. I had AI walk me through the process. It taught me about the yard line vs. under-slab distinction, and suggested getting just the yard line replaced first because it's much cheaper and can fix the issue. I did that and spent $6k. The issue was fixed. I "saved" $30k for now by deferring that massive month-long project. (For brevity, I'm omitting a ton of boring technical stuff I learned about plumbing that helped me make the optimal decision - none of the contractors bothered explaining any of it.)

- My 2010 Hyundai Santa Fe is starting to show its age. I've taken it to multiple different repair shops, then fed their diagnoses and recommendations to AI and figured out which ones are trying to fleece me and which ones are being more careful and conservative with their repair recommendations. Probably saved several thousand dollars there. Learned a lot about cars too!

- My partner and I are converting the backyard to a wildlife sanctuary. The AI helped us plan what to plant where (depending on lots of factors like sunlight location, irrigation access, etc.) and it has been going really well. Also planned out a dragonfly pond to deal with mosquitoes. AI created a project plan, including schematics, material purchase list and step-by-step instructions.

- I've been wanting to do various other home improvement projects, but only ones that make financial sense. I took photos of my house, both inside and outside, and fed them to AI, and said "give me a list of projects I can do that will have high ROI for when I decide to sell this house". It spent 15 mins doing deep research, then came back with a long, prioritized list. If I do all the projects, I'd be spending about $40k and it would improve the house valuation by about $90k.

I can go on. There's probably dozens of stuff that I've used it for over the past year that led to massive time and money savings, and I've learned a ton as well about topics I normally would not have been exposed to or bothered to research myself. And I'm not even including all the work-related usage, both for my employer and my side business. That would be its own very long list.

Articles that start with no are inherently biased and only gather reads from people that agree.

or for anything

The numbers given in the article are actually consistent with what is usually meant by “everyone” in such statements. Sure, it’s not literally everyone. But it’s a very significant percentage, especially given how quick the adoption has been.

> AI has gotten so good

Actually anything that is about 90% great and 10% disastrously wrong is utter crap given the way people want and do use AI models.

They are great tools in the right hands and awful in the wrong.

I honestly just use it as a search engine to get around SEO garbage and ads.

My wife uses it for a (non-computer related) business though and it's great for all sorts of normally tedious marketing/social media type jobs though. Stuff that doesn't really require accuracy just needs text on pictures that looks good quickly.

I think everyone just has FOMO and doesn't want to lose to competitors. Eventually it'll die down.

"Think of how stupid the average person is, and realize half of them are stupider than that."

Bit of an odd decision to build an entire article around a clickbait headline from July 2025. Talk about a strawman.

That aside, this piece is interesting and ties together some useful numbers and studies.

I hadn't seen the recent Microsoft paper showing:

> 30 percent of the US working-age population is using AI [...] with at least 90 minutes of usage time in a given month.

I'm honestly impressed at how high that number is! That's a lot of adoption for a technology (LLM chatbots) that didn't exist four years ago.