A revolution means radical changes executed over a short period of time. Well with 4 years in, this has got to be one of the smallest "revolutions" we have ever witnessed in human history. Maybe it's revolutionary for people who get excited about crappy pictures they can insert into their slides to impress the management.
They put these stories out just to make the general public (who might not understand that this is just bs) but makes AI seem scary so people get a lopsided view of AI and capacities that are straight out of science fiction.
Millions is an understatement on how much AI marketing spend is
IBM sees the funding bubble bursting and the next wave of AI innovation as about to begin.
IBM was too early with "Watson" to really participate in the 2018-2025 rapid scaling growth phase, but they want to be present for the next round of more sensible investment.
IBM's CEO is attempting to poison the well for funding, startups, and other ventures so IBM can collect itself and take advantage of any opportunities to insert itself back into the AI game. They're hoping timing and preparation pay off this time.
It's not like IBM totally slept on AI. They had Kubernetes clusters with GPUs. They had models and notebooks. But their offerings were the absolute worst. They weren't in a position to service real customers or build real products.
Have you seen their cloud offerings? Ugh.
They're hoping this time they'll be better prepared. And they want to dunk on AI to cool the playing field as much as they can. Maybe pick up an acquisition or two on the cheap.
How exactly are they poisoning the well..? OpenAI committed to 1.4 trillion investements...with a revenue of ~13B - how is IBM CEO contributing to that absolutely already poisoned situation? Steve Jobs did not care about naysayers when he introduced iPhone - because his product was so innovative for the time. According to AI boosters, we now have a segment of supposedly incredibly powerful and at the same time "dangerous" AI products. Why are they not sweeping the floor off with the "negators", "luddites", "laggards" etc... After so many hundreds of billions of dollars and supposedly so many "smart" AI researchers...Where are the groundbreaking results man? Where are the billion-dollar startups launched by single persons (heck, I'd settle even for a small team)...Where are the ultimate applications..etc?
I pay for YouTube Premium too (probably not much longer) but can only 'comfortably' use the site through a series of increasingly hacky extensions for Firefox. On non-web apps, there is no recourse from the UI enshittification.
The general theme is the same as the article: less real estate dedicated to actual videos you might want to watch. There were two rows of completely useless garbage that I had to add to my uBlock Origin filter just now: one for Shorts (which I have blocked in the past) and a new one for some sort of Youtube Games thing (?) that looked like the worst AI generated slop you'd never want to play.
If this is the premium experience then I don't want it.
> The general theme is the same as the article: less real estate dedicated to actual videos you might want to watch. There were two rows of completely useless garbage that I had to add to my uBlock Origin filter just now: one for Shorts (which I have blocked in the past) and a new one for some sort of Youtube Games thing (?) that looked like the worst AI generated slop you'd never want to play.
This is the same stuff you get without buying Premium. So I guess they figure you're only paying to dodge the ads.
Which seems, to me, like a lot of money compared to (ad cost * number of ads you would see).
There is a prevailing mentality that LLMs make it easy to become productive in new languages, if you are already proficient in one. That's perhaps true until you suddenly bump up against the need to go beyond your superficial understanding of the new language and its idiosyncrasies. These little collisions with reality occur until one of them sparks an issue of this magnitude.
In theory, experienced human code reviewers can course correct newer LLM-guided devs work before it blows up. In practice, reviewers are already stretched thin and submitters absolute to now rapidly generate more and more code to review makes that exhaustion effect way worse. It becomes less likely they spot something small but obvious amongst the haystack of LLM generated code bailing there way.
> There is a prevailing mentality that LLMs make it easy to become productive in new languages, if you are already proficient in one.
Yes, and: I've found this to be mostly true, if you make sure you take the time to deeply understand what the code is doing. When I asked an LLM to do something for me in Javascript, then I said, "What if X happens, wouldn't that cause Y? Would it be better to restructure it like so and so to make it more robust?" The LLM immediately improves it.
Any experienced programmer who was taking the time to review this code, on learning that unwrap() has a "panic" inside, would certainly change it. But as you say, reviewers are already stretched thin.
> * A thin glue layer orchestrating all of the above: injecting the list of available tools into the LLM context, parsing LLM output to detect tool calls and invoke them with appropriate args, and inject results back into LLM context
Yeah llm rules. You think there must be something more to it. There's not.
For cache, having TTL is invaluable. Having to tune cleanup jobs in Postgres is annoying. Deletes create dead rows (so do updates) so now you have to deal with vacuum as well. The method the author suggested will run into a lot more problems if the service ever needs to scale up beyond what they estimated than a traditional dedicated cache like Redis in front.
Looking a little deeper, the author's written a scattering of blog posts in the past 3 years, and has spent seemingly little more time as a professional software developer versus finance/business. Not jaded enough yet for senior
Does anybody really believe that SalesForce of all companies has successfully replaced 4000 real and necessary jobs with AI? Or is that more likely just an excuse to justify more layoffs in the tech industry for the usual reasons.
tbh. for companies like SalesForce I always assume they have a lot of bloated unnecessary jobs which are done well enough by the people having them to needing a external reason to firing them
in addition SalesForce grew in employment size in 2025 AFIK and 4000 jobs are for them only around ~~5%, which means it's to small to be a meaningful metric if you don't fully trust what their press department does (and you shouldn't)
still I see people using modern AI for small productivity boosts all over the place including private live (and often with a wastely underestimate risk assessment) so in the best case it's only good enough to let people process more of the backlog (which otherwise would be discarded due to time pressure but isn't worthless) and in the worst case will lead to idk. 1/3 of people in many areas losing their job. But that is _without_ major breakthrough in AI, just based one better applying what AI already can do now :/ (and is excluding mostly physical jobs, but it's worse for some other jobs, like low skill graphic design positions)
During the just-post-pandemic hiring spree I remember talking to some software developers who were doing very light coding in what I would usually think was a business analyst role. Those roles were both bloat that was lost once free money stopped flowing, and easily replaced (or reduced) with AI.
And as software developers, it would be silly if we didn't think that businesses would love to find a way to replace us, as the software we have created did for other roles for the past 60 years.
I really wish journalists & public speaking investors would call this out more.
Though like non-GAAP earnings & adjusted EBITDA, very few care. Those that do are often old, technical, conservative & silent type of investors instead of podcasters or CNBC guests. RIP Charlie M.
There's no doubt it can function as a convenient cover, but that doesn't mean it's having no effect at all. It would be naive to assume that the introduction of a fundamentally new general-purpose work tool across millions of workers in nearly every industry and company within the span of a couple years has not played any role whatsoever in making teams and organizations more efficient in terms of headcount.
They did say this was specifically in customer service, which if there was a department I believe you might be replaced by AI this would be it;
Alternatively though if the market is bad and there not launching as many new products or appealing to as many new customers, customer support may be a cost center you’d force to have “AI efficiencies”
It's less about justifying layouts and more PR: Salesforce is trying to sell AI products and they're marketing how good they are at AI by saying they removed 4k jobs with it
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