If nothing else, the timing is suspect given the attention and press open weight models are getting over the last few weeks. The releases of Kimi and other models is getting open weight models enough attention that the US government, perhaps pushed by OpenAI and Anthropic, to think about taking action against these models for security concerns.
Good to see that more neutral companies (Microsoft and Meta to name two) are pushing back against US government involvement:
Yeah came here to say the same thing on the lack of absolute units.
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.
Agreed and it's unlikely to slow down that descent into slop coding until there are some visible issues with it. The market (i.e. companies) are going all in on AI coding because everyone else is doing it and the concern (understandably) is that if a company doesn't join that race they will lose because they never even entered the race.
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.
> There's a world of difference between managing a dozen or so individual contributors vs managing senior managers / directors.
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.
Sure, still need to enable access the same info but feels like bucketing the clients into
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.
Per a report that came out the other day, the GitHub move to Azure has been slowed down (i.e. I don't think it's done). But maybe you have newer/better info than me
Yeah, that and Microsoft has been slow to move the infrastructure to something that scales better to handle that load.
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.
> Every use of AI for these robs the employee culture of a genuine trust building moment.
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".
> This sounds like an attempt to rationalize the fact that your business isn't that effective, otherwise adding more people would result in making more money.
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.
+1 to all of this. The challenge can be staying focused and thinking when the AI assistant is (1) moving very fast and (2) often times doing multiple things at the same time.
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.
From reading the text of the article, and the direct quotes, I'm also unclear on why they booed him.
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.
New knowledge doesn't necessarily push out old knowledge, and we probably don't have infinite capacity for knowledge. That being said, at least in my experience, the time when new pushes out old is when old is less useful than new.
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.
Relatable! Or at least making me feel dumb (at times). Things that help me feel smarter are
* 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 problem with the current political situation/administration in the US is that there's so much existing conflict of interest going on that anytime the government investigates concerns about conflict of interest, it feels politically motivated because of the uneven investigation.
Unless I'm missing something, the linked article from MIT is about more than graduate students. That article talks about how changes introduced in 2025 are causing taxation on budgets that (as far as I can tell) affect all students.
The prior poster is making the case that might not be a bad thing, but its not just graduate students
Yeah, conceptually this isn't all that different from new VM SKUs coming out in clouds. The costs and rate of change for AI hardware may be higher, and perhaps enough higher to mess up the math, but conceptually its a model that has been proven to work.
Yeah that's a good callout for sure, the spending here is nuts so agree that it's not "just another business that has to price itself right to be competitive".
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.
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...