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.
As long as Apple and Google put reasonable AI capabilities on device, then software engineers will use those capabilities when it makes sense (the article gives lots of good examples of capabilities that make sense to run locally). As the author notes, it's cheaper and more reliable to run these things locally.
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.
The article is good in that it highlights the need for AI agents/assistants to help with different parts of software development, not just the up front "build me a new widget" part. The author (correctly imo) frames that if someone just uses an AI agent/assistant at the new widget part, then they'll end up with a lot more code to maintain since with AI, they crank out more code. Even if it's high quality, there is maintenance cost over time.
That being said, the problem the author talks about is more of a self imposed thing than everyone is going to suffer thing. The author correctly points out the startup scenario, where its just "get this damn thing to work somehow so I can see if there's market fit and nab some customers". That scenario has typically always come with higher maintenance costs down the road because quality is (rightfully) lowered in the name of speed to see if there's a business and if there is, get it going.
Also felt like the author was reluctant to talk about how AI can actually help with the maintenance part. AI can be great at fixing old dependencies and annoying bugs (with human guidance). Those tasks can feel like toil for software engineers and the kinds of things a software engineer will want AI to help with
> My point is that maybe it was intentional, but just bad UX culture.
This may be valid, but even if it is someone (or a group of people) at Amazon are violating one of their core leadership principles - Customer Obsession
A useful (and hopefully delightful) UX is key to showing customer obsession.
That being said, I personally feel the UX at Amazon sucks overall, not just for pricing/packaging but even getting basic shit done. So perhaps Amazon (or at least AWS) doesn't think a good UX is a key ingredient to demonstrating Customer Obsession.
So the reduction gets them closer, but still higher than where they were in 2024. Given the fact that the crypto business doesn't seem to be growing much over the last few years it can be argued that they over hired in 2025 and going back to 2024 numbers just makes sense. And as others have said in the comments, they haven't turned a profit so likely this makes business sense and the AI shine is trying to make the news less ugly for investors.
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.