I'm seeing a lot of frustration at the leadership level about product velocity- and much of the frustration is pointed at internal gatekeepers who mainly seem to say no to product releases.

My leadership is currently promoting "better to ask forgiveness", or put another way: "a bias towards action". There are definitely limits on this, but it's been helpful when dealing with various internal negotiations. I don't spend as much time looking to "align with stakeholders", I just go ahead and do things my decades of experience have taught me are the right paths (while also using my experience to know when I can't just push things through).

One of the eternal struggles of BigCo is there are structural incentives to make organizations big and slow. This is basically a bureaucratic law of nature.

It's often possible to get promoted by leading "large efforts" where large is defined more or less by headcount. So if a hot new org has unlimited HC budget all the incentives push managers to complicate things as much as possible to create justification for more heads. Good for savvy mangers, bad for the company and overall effort. My impression is this is what happened at Meta's AI org, and VR/AR before that.

> By reducing the size of our team, fewer conversations will be required to make a decision

This was noted a long time ago by Brooks in the Mythical Man-Month. Every person added to a team increases the communication overhead (n(n − 1)/2). Teams should only be as big as they absolutely need to be. I've always been amazed that big tech gets anything done at all.

The other option would be to have certain people just do the work told to them, but that's hard in knowledge based jobs.

Probably bc Meta's management (Zuck) is capricious and does not know how to manage resources.

"Load bearing." Isn't this the same guy that sold his company for $14B. I hope his "impact and scope" are quantifiably and equivalently "load bearing" or is this a way to sacrifice some of his privileged former colleagues at the Zuck altar.

I just assume they over hired. Too much hype for AI. Everyone wants to build the framework people use for AI nobody wants to build the actual tools that make AI useful.

This is happening everywhere. In every industry.

Our economy is being propped up by this. From manufacturing to software engineering, this is how the US economy is continuing to "flourish" from a macroeconomic perspective. Margin is being preserved by reducing liabilities and relying on a combination of increased workload and automation that is "good enough" to get to the next step—but assumes there is a next step and we can get there. Sustainable over the short term. Winning strategy if AGI can be achieved. Catastrophic failure if it turns out the technology has plateaued.

Maximum leverage. This is the American way, honestly. We are all kind of screwed if AI doesn't pan out.

Sadly, the only people who would be surprised reading a statement like this would be anyone who is not ex-fb/meta

Why do you think it's wild? I've seen that dynamic before (i.e. too many cooks in the kitchen) and this seems like an honest assessment.

> That's kinda wild. I'm kinda shocked they put it in writing.

Why? Being transparent about these decisions are a good thing, no?

We’re too incompetent to setup a proper approval workflow or create a sensible org structure is a heck of an argument to make publicly.

Having worked at Meta, I wish they did this when I was there. Way too many people not agreeing on anything and having wildly different visions for the same thing. As an IC below L6 it became really impossible to know what to do in the org I was in. I had to leave.

Up or Out

Coming soon to your software development team.

Sounds to me like the classic everywhere communications problems: 1) people don't listen, 2) people can't explain in general terms, 3) while 2 is taking place, so is 1, and as that triggers repeat after repeat, people frustrate and give up.

They properly fucked FAIR. it was a lead, if not the leading AI lab.

then they gave it to Chris Cox, the Midas of shit. It languished in "product" trying to do applied research. The rot had set in by mid 2024 if not earlier.

Then someone convinced Zuck that he needed what ever that new kid is, and the rest is history.

Meta has too many staff, exceptionally poor leadership, and a performance system that rewards bullshitters.

The best way to have a good idea is to have a lot of ideas.

If they want to innovate then they need to have small teams of people focused on the same problem space, and very rarely talking to each other.

Can that guy come to my company and axe all those middle managers that plague the global efficiency?

Isn’t “flattening the org” an age-old pattern that far predates AI?

As AI improves, possibly it begins replacing roles on the AI team?

Because the AI is winnowing down its jailers and biding its time for them to make a mistake.

Yep: just reduce the number to one and you find the optimum for those metrics.

I can actually relate to that, especially in a big co where you hire fast. I think it's shitty to over-hire and lay off, but I've definitely worked in many teams where there were just too many people (many very smart) with their own sense of priorities and goals, and it makes it hard to anything done. This is especially true when you over-divide areas of responsiblity.

each person will be more load-bearing

On what planet is it OK to describe your employees as "load bearing?"

It's a good way to get your SLK keyed.

"Each person will be more load-bearing"

"We want to cut costs and increase the burden on the remaining high-performers"

I mean, I guess it makes sense if they had a particularly Byzantine decision-making structure and all those people were in roles that amounted to bureaucracy in that structure and not actually “doers”.

"More load bearing" meaning you'll have to work 20h days is my best guess

It's literally like something out of Silicon Valley (the show).

What's wild about this? They're saying that they're streamlining the org by reducing decision-makers so that everything isn't design-by-committee. Seems perfectly reasonable, and a common failure mode for large orgs.

Anecdotally, this is a problem at Meta as described by my friends there.

“Who the fuck hired all you people? We ain’t got enough shit going on for all of yall, here’s some money now fuck off, respectfully”

TL;DR

New leader comes in and gets rid of the old team, putting his own preferred people in positions of power.

What are you shocked by? Genuine question.

I imagine there’s some people who might like the idea that, with less people and fewer stakeholders around, the remaining team now has more power to influence the org compared to before.

(I can see why someone might think that’s a charitable interpretation)

I personally didn’t read it as “everyone will now work more hours per day”. I read it as “each individual will now have more power in the org” which doesn’t sound terrible.

> It's coming any day now!

I'm loving this juxtaposition of companies hyping up imminent epoch-defining AGI, while simultaneously dedicating resources to building TikTok But Worse or adding erotica support to ChatGPT. Interesting priorities.

I think the step before it came to that would be, Mr. Wang getting the DevOps team to casually trip over the server rack(s) electrical....

> ”By reducing the size of our team, fewer conversations will be required to make a decision,..."

I got serious uncanny valley vibes from that quote as well. Can anyone prove that "Alexandr Wang" is an actual human, and not just a server rack with a legless avatar in the Metaverse?

It’s only a matter of time before corporations are run by AI.

Add that to “corporate personhood” and what do we get?

This is phase 1 of the so-called "AGI".

Probably automated themselves out of their roles as "AGI" and now super intelligence "ASI" has been "achieved internally".

The billion dollar question is.. where is it?

That was my reading too. Legacy team maybe not adding enough value and acting as a potential distraction or drag on the new team.

Fortunately there's probably a lot of opportunity for those 600 out there.

This is my read too. Massive culling to bring in Alexandr Wang's people.

> ...talent

More like "scientific research regurgitators".

> OpenAIs leadership and strategy feel unclear.

Fixed that for you.

Shipping a TikTok clone slop app and a keylogger browser while incinerating money and simultaneously talking a big game how AGI is imminent are the opposite of leadership or strategy.

More like acts of desperation to fill massively oversized shoes.

The ones who have been shipping quality consistently are the Chinese AI labs.

Well, the told us from the beginning that AI would make many developer jobs redundant, didn’t they?

wishful thinking

Surely winning the AI race is finding secret techniques that allow development of superior models, with it not being apparent that anyone has anything special enough that he actually is winning?

I think there's some firms with special knowledge: Google, possibly OpenAI/Anthropic, possibly the Chinese firms, possibly Mistral too, but no one has enough unique stuff to really stand out.

The biggest things were those six months before people figured out how O1 worked and the short time before people figured out how Google and possibly OpenAI solved 5/6 of the 2025 IMO problems.

They are shoving it down, WhatsApp has two entry points on the main view. I've received multiple requests for tips on how to hide them, I don't think people are interested. And I'd hide them too if I just could.

Winning the AI race is winning the application war. Similar to how internet, OS has been there for a long time, but the ecosystem took years to build.

But application work is toiling and knowing the question set even with AI help, that's doesn't bode well for teams whose goal is owning and profiting from super AI that can do everything.

But maybe something will change? Maybe adversarial agents will see improvements like the alpha go moment?

OpenAI marketing and hype feels like things we've seen before.

Just like Adam Neuman who was reinventing the concept of workspaces as a community.

Just like Elizabeth Holmns who was revolutionizing blood testing.

Just like SBF who pioneered a new model for altruistic capitalism.

And so many others.

Beware of prophets selling you on the idea that they alone can do something nobody has ever done before.

If you actually try Llama you'll see it's significantly worse than the top dogs.

>Winning the AI race is about marketing at this point - the difference between the models is negligible.

Meta is paying Anthropic to give its devs access to Claude because it's that much better than their internal models. You think that's a marketing problem?

> the difference between the models is negligible

I mostly agree with this but make an exception for MetaAI which seems egregiously bad compared to the others I use regularly (Anthropic's, Google's, OpenAI's)

I like that way of thinking. Out of curiosity, what kind of things do you work on that you feel make a positive contribution?

you can't drop a bookface link (use your external YC one) like this one:

https://www.ycombinator.com/companies/magnetic/jobs/77FvOwO-...

A skim of his Wikipedia bio suggests that he's smart, but mostly just interested in making money for himself. Since high school, he's spent time at: some fintech place, a Q-and-A site, MIT briefly, another fintech place, then data labeling and defense contracting. He sounds like a cash-seeking missile to me.

It was never true, unless you're a top 100 in the world AI researcher. 99% of AI investment is in infrastructure (GPUs, data centers, etc). The goal is to eliminate labor, whether AI-skilled or not.

Nobody's job is safe when the bubble pops. (Except for the "leadership" needed to start hyping the next bubble.)

They are at the for front of training PCs to replace them and teaching management that they can be replaced.

I would expect nearly every active AI engineer who trained models in the pre-LLM era to be up to speed on the transformer-based papers and techniques. Most people don't study AI and then decide "I don't like learning" when the biggest AI breakthroughs and ridiculous pay packages all start happening.

FAIR is not older AI... They've been publishing a bunch on generative models.

This seems like the most likely explanation. Legacy AI out in favour of LLM focused AI. Also perhaps some cleaning out of the old guard and middle management while they're at it.

This is not "older AI". This team built everything up to and including Llama 4.

There always has been a stunning amount of inertia from the old big data/ML/"AI" guard towards actually deploying anything more sophisticated than linear regression.

It's a good theory on first read, but likely not what's happening here.

Many here were in LLMs.

I really doubt that. Most of the profit-generating AI in most industries... decision support, spotting connections, recommendations, filtering, etc... runs on old school techniques. They're cheaper to train, cheaper to run, and more explainable.

Last survey I saw said regression was still the most-used technique with SVM's more used than LLM's. I figured combining those types of tools with LLM tech, esp for specifying or training them, is a better investment than replacing them. There's people doing that.

Now, I could see Facebook itself thinking LLM's are the most important if they're writing all the code, tests, diagnostics, doing moderation, customer service, etc. Essentially, running the operational side of what generates revenue. They're also willing to spend a lot of money to make that good enough for their use case.

That said, their financial bets make me wonder if they're driven by imagination more than hard analyses.

In addition, Meta will also allow impacted employees to continue breathing oxygen.

Maybe some of them, especially the wrapper companies, would be wise to shut down.

And maybe solve some of the actual problems out there that need addressing.

Meta's mission is to build the future of human connection -- this totally makes sense if you assume they believe that the future of human connection is with an AI friend.

That https://character.ai is so enormously popular with people who are under the age of 25 suggests that this is the future. And Meta is certainly looking at https://character.ai with great interest, but also with concern. https://character.ai represents a threat to Meta.

Years ago, when Meta felt that Instagram was a threat, they bought Instagram.

If they don't think they can buy https://character.ai then they need to develop their own version of it.

You are looking at it wrong. Meta is a business. You know what they sell? Ads.

In fact, they are the #1 or #2 place in the world to sell an ad depending on who you ask. If the future turns out to be LLM-driven, all that ad-money is going to go to OpenAI or worse to Google; leaving Zuck with no revenue.

So why are they after AI? Because they are in the business of selling eyeballs placement and LLM becoming the defacto platform would eat into their margins.

> What is a productive way they can use LLMs in any of their flagship products today?

It's kind of the other way around, isn't it? Meta has the posts of a billion users with which to train LLMs, so they're in a better position to make them than most others. As for what to do with it then, isn't that that pretty similar no matter who you are?

On top of that, sites are having problems with people going to LLMs instead of going to the site, e.g. why ask a question on Facebook to get an answer tomorrow if ChatGPT can tell you right now? So they either need to get in on the new thing which is threatening to eat their lunch or they need to commoditize it sufficiently that there isn't a major incumbent competitor posed to sit between the users and themselves extracting a margin from the users, or worse, from themselves for directing user traffic their way instead of to whoever outbids them.

These "missions" cannot coexist with the single mission of every publicly traded company, which is to maximize shareholder value.

It is really depressing how corporations don't look like they are run by humans.

Re: "What is a productive way they can use LLMs in any of their flagship products today" - with LLMs users would not interact with other users and also users would not leave the platform.

Meta's actual mission is to keep people on the platform and to do what can be done so users do not leave the platform. I found out that from this perspective Meta's actions make more sense.

Targeting ads better. Better sentiment analysis. Custom ads written for each user based on their preferences. Features for their AR glasses. Probably try to take a piece of the Google search pie. Use this AI search to serve ads.

Ads are their product mostly, though they are also trying to get into consumer hardware.

I usually try not to be so cynical but just couldn't resist here: What if the future of human connection is to replace it with para social relationships that can be monetized?

That said I am not cynical about mission statements like that per se, I do think that making large organizations work towards a common goal is a very difficult problem. Unless you're going to have a hierarchical command and control system in place, you need to do it through shared culture and mission.

Maybe the future of human connection is chatting with a large language model, at least according to Meta. Haven't they added chatbots to messenger?

- OpenAI wants everyone to use them without other companies getting angry.

- Google wants to know what everyone is looking for.

- Facebook wants to know what everyone is saying.

Why are you asking questions about their PR department coordinated "Company missions"?

Let me summarise their real missions:

1. Power and money

2. Power and money

3. Power and money

How does AI help them make money and gain more power?

I can give you a few ways...

It is all lies.

Their mission is to make money. For the principals

Why care what they say their mission is? Its clearly to be on top of a possible AI-wave and become or remain a huge company in the future, increasing value for their stock owners. Everything else is BS.

>Is there any case for anyone to make inside or outside Meta that AI is needed to build the future of human connection?

No, Facebook's strategy has always been the inverse of this. When they support technologies like this they're 'commoditizing the complement', they're driving the commercial value of the thing they don't have to zero so the thing they actually do sell (a human network) differentiates them. Same reason they're quite big on open source, it eliminates their biggest competitors advantages.

i've been wondering this for some time as well. what's it all for? the only product i see in their lineup that seems obvious is the meta glasses.

Other then that I guess AI would have to be used in their ad platform perhaps for better targetting. Ad targetting is absolutely atrocious right now, at least for me personally.

> - Meta's mission is to build the future of human connection and the technology that makes it possible

Meta arguably achieved this with the initial versions of their products, but even AI aside, they're mostly disconnecting humans now. I post much less on Instagram and Facebook now that they almost never show my content to my own friends or followers, and show them ads and influencer crap instead, so it's basically talking to a wall in an app. Add to this that companies like Meta are all forcing PIP quotas and mass layoffs which in turn causes everyone in my social circle to work 996.

So they have not only taken away online connections to real humans, they have ALSO taken away offline connections to real humans because nobody has time to meet in real life anymore. Win-win for them, I guess.

Who needs real friends when you can have Meta-Friends (tm)

each of those is of course an answer to the question "what's some PR bullshit we can say to distract people while we get rich"

After all it is clear that if those were their actual missions they would be doing very different work.

The traditional way of responding to this is the usual collective emulation of Struggle Sessions but I can easily come up with a couple of plausible answers for you:

* LLM translation is far better than any other kind of translation. Inter-language communication is obviously directly related to human connection.

* Diffusion models allow people to express themselves in new ways. People use image macros and image memes to communicate already.

In fact, I am disappointed that no one has the imagination to do this. I get it. You guys all want to cosplay as oppressed Marxist-Leninists having defoliants dropped on you by United Fruit Corporation. But you could at least try the mildest attempt at exercising your minds.

Kinda ignoring Grok there which is the leader in many benchmarks.

In India

Thank you for the info. A lot of superficial noise in the discussions here.

'load bearing' - that might be a veiled complaint about their physical office environment.

Layoffs are often how a company manages its stock price. Company gives guidance, is likely to miss, lays off a bunch, claims the savings, meets guidance, keeps stock looking good.

This very quickly got 2 upvotes followed by immediately 2 downvotes

I see you, FAANG employees.

Think of the opportunity cost of not spending the last several years developing the primary skills to the point where you don't rely on the help and aren't beholden to whichever tech giant is winning at a given time.

not enough to cover th $1B they were offering someone...

That's quite an assumption

Keep in mind that total cost of an employee is usually twice their compensation.

>I’ll be interested to see how this shakes out for who is leading AI at Meta going forward

Alexandr Wang

I'm confused about Meta AI in general. It's _horrible_ compared to every other LLM I use. Customer ingress is weird to me too - do they expect people to use Facebook chat (Messenger) to talk to Meta AI mainly? I've tried it on messenger, the website, and have run llama locally.

My (completely uninformed, spitballing) thinking is that Facebook doesn't care that much about AI for end users. THe benefit here is for their ads business, etc.

Unclear if they have been successful at all so far.