voncheese
Your comment about Amazon sucking resonated as I recently talked with them about a job, but walked away being super disinterested. I do not think this is an Amazon problem (fwiw, I worked at Microsoft for a super long time), I think it's a "problem" with the massive success of technology in the world.
Back in the day of NeXT, Be and early Apple, it was alot about building something cool and fun and a less about the huge money that could/would be made. Now the whole world relies on technology and there is so much money that the environment of a tech company is alot more about the business than it is the technology.
I personally don't think thats necessarily a bad thing, it's just evolution of the technology business.
Grand Day Out is a fantastic watch, the animation, characters and story telling are so fun for really anyone of any age.
In order to learn and improve you have to know what went wrong, with AI being personified and pulled into the pool of entities that may be at fault, it makes it harder to figure out what actually went wrong and learn. Not impossible to figure out, just harder.
I really like this simple statement. It gets to the heart of what is bad about social media (at least to me). Its one thing if a site has the same content that I have to actually go and crawl through myself to find things that interest me, its another when the site thinks it knows what I want/like and guides me.
The former forces me to engage my brain and explicitly engage with content (good or bad) the latter enables my brain to implicitly engage with content (good or bad).
Thank you for the statement!
That makes it way more likely that people blame AI (doesn't make it right by any means, but does mean that the actual blame gets diffused even more).
Also goes to show how hard it is to predict anything that is a massive change - these levels of changes are so infrequent that we can't rely on priors to predict the future.
Case in point, I make a daily playlist for running and that UX is frequently changing and often for the worse, but I deal with it because it's a habit that costs me a few seconds maybe a minute per day. The cost of switching to a new thing just feels daunting so I stay.
I also am guilty of enjoying the wrapped summaries at the end of the year :)
Good to see that more neutral companies (Microsoft and Meta to name two) are pushing back against US government involvement:
https://www.cnbc.com/2026/07/24/nvidia-microsoft-meta-open-w...
Speaking as an older vinyl collector myself, with kids who have also gotten into it...it would surprise me if the total unit numbers were even within 2 orders of magnitude.
Vinyl just feels different. The feeling of holding the cardboard cover and the weight of the album on a turntable can't be replicated at all with CDs.
The trick will be for companies to go fast enough to be in the race, not winning it, just in it. That will allow the time/space to let someone else, whoever is going fastest, to trip and fall so the rest of the pack can learn.
The tip and fall moment could come as a major incident (reliability and/or security) or loss of revenue because of bad products that customers don't like enough to use.
I agree, but in my opinion, your point about needing to know how things work still holds. It's less relevant as you move up to managing managers and larger orgs, but it never goes to zero if you're going to be successful.
Will it be is a different thing though. And if it’s not, who exactly is accountable?
With funds and portfolio managers that run them, there’s a clear accountability model (if the fund sucks, the manager loses their job and the company loses credibility)
With AI agents doing the management, who is accountable when the fund sucks? If it’s the customer, we’ve moved accountability from someone who at least in theory, knows what they’re doing to someone who has little to no clue.
bucket1 = clients that were working just fine before (users and whatever automation they had in place) bucket2 = ai clients that contributed to, if not flat out caused, the scale problems
then slowing down/limiting the bucket2 clients while keeping the bucket1 clients rolling as-is, is both doable and keeps existing customers happy while the underlying infra gets scale/perf improvements needed to support ai clients at scale.
The more surpassing part is that Microsoft hasn't figured out a way to manage/contain the AI-sourced traffic better so it doesn't create all this noisy neighbor problems for non-AI usage/users.
Spot on.
The erosion of communication and relationships between people in the workplace (or even outside it) that AI contributes to is something that we don't talk about nearly enough. Society today has already suffered greatly in these areas thanks to social media, and AI just makes it worse.
People (in general) are really struggling to understand when/how to use AI to be more productive and happier (and imo there is a way to do it, by offloading the grunt work to AI). With the constant rush and jamming of AI down everyone's throats though, its hard to be able to take that step back and think "is this use of AI making me happier/more productive".
Thanks for sharing!
Yes, or that businesses are expecting a slow down in the economy that hinders their ability to sell (i.e. their customers are going to cutback on spending)
This was the case last year (or maybe it was the year before) where technology companies saw their customers reducing spend and tightening belts.
The current economy feels hard to figure out, in that the market keeps going up but so is inflation and the struggle of the everyday American at least.
Perhaps that is leading technology companies to be more conservative in how much they produce.
The job impact is really pissing people off, rightfully so.
I know I have struggled to keep up, and fall into the trap of approving things (either commands or recommendations) without taking the time to really process and think about them.
It's a bit like the age old problem of "it's super easy to ask questions, and can be super hard to answer many of them". So the economy of the conversation gets out of whack fast.
My guess is because of what he's done, or at least perceived to have done, in the area of AI. Because what he said (at least to me) didn't seem boo-worthy, but in the context of who is saying it, I can see it.
Put another way, if someone that the audience liked said the same things, its not clear the person would get booed.
Retaining (again just speaking for myself) requires actually using / applying the knowledge at some point within some timeframe of learning it. Otherwise yeah it fades to the point of disappearing over time.
* actually writing more on my own - created a personal blog just to get myself to write more
* upleveling my thinking - think more about problems and framing
* leverage my experience - guide (or sometimes force) the AI assistant to leverage my experience to avoid problems
* learning new things - rather than let AI just replace things I can do, I use AI to help me learn new things/technology faster than I would have pre-AI
The prior poster is making the case that might not be a bad thing, but its not just graduate students
I guess if the time horizons is long, like 20 years, then maybe the spending, as it begins to amortize, gets more in line?
I was thinking that a comparison could be to cloud providers, each of which had to spend a lot of money to build out datacenter before making money. Difference there is AWS proved the product first, so when Microsoft and Google came along, they knew it would work and be profitable. With AI, nobody has proven it will work and be profitable, they're all competing for that at the same time which is a potentially dangerous mix for the reasons you cited.
That also doesn't preclude LLM services from being massively successful, they'll just have to justify the pricing and complexity that comes with their adoption, just like any other product.