92 comments

[ 2.5 ms ] story [ 68.7 ms ] thread
Maybe I’m paranoid but this sounds too good to be true. Almost like something planted to help with recruiting after meta poached their best guys.
> The Codex sprint was probably the hardest I've worked in nearly a decade. Most nights were up until 11 or midnight. Waking up to a newborn at 5:30 every morning. Heading to the office again at 7a. Working most weekends.

There's so much compression / time-dilation in the industry: large projects are pushed out and released in weeks; careers are made in months.

Worried about how sustainable this is for its people, given the risk of burnout.

> The thing that I appreciate most is that the company is that it "walks the walk" in terms of distributing the benefits of AI. Cutting edge models aren't reserved for some enterprise-grade tier with an annual agreement. Anybody in the world can jump onto ChatGPT and get an answer, even if they aren't logged in.

I would argue that there are very few benefits of AI, if any at all. What it actually does is create a prisoner's dilemma situation where some use it to become more efficient only because it makes them faster and then others do the same to keep up. But I think everyone would be FAR better off without AI.

What keeping AI free for everyone is akin to is keeping an addictive drug free for everyone so that it can be sold in larger quantities later.

One can argue that some technology is beneficial. A mosquito net made of plastic immediately improves one's comfort if out in the woods. But AI doesn't really offer any immediate TRUE improvement of life, only a bit more convenience in a world already saturated in it. It's past the point of diminishing returns for true life improvement and I think everyone deep down inside knows that, but is seduced by the nearly-magical quality of it because we are instinctually driven to seek out advantags and new information.

What’s the GTM role referenced a couple of times in the post?
This was good, but the one thing I most wanted to know about what it's like building new products inside of OpenAI is how and how much LLMs are involved in their building process.
(comment deleted)
(comment deleted)
wham. thanks for sharing anecdotal episodes from OAI's inner mecahnism from an eng perspective. I wonder if OAI wouldn't be married to Azure would the infra be more resilient, require less eng effort to invent things to just run (at scale).

What i haven't seen much is the split between eng and research and how people within the company are thinking about AGI and the future, workforce, etc. Is it the usual SF wonderland or is there an OAI specific value alignment once someone is working there.

Whoa, there is a ton of interesting stuff in this one, and plenty of information I've never seen shared before. Worth spending some time with it.
Granted the "OpenAI is not a monolith" comment, interesting that use of AI assisted coding was a curious omission from the article -- no mention if encouraged or discouraged.
Interesting how ChatGPT’s style of writing has made people start bolding so much text.
"Safety is actually more of a thing than you might guess if you read a lot from Zvi or Lesswrong. There's a large number of people working to develop safety systems. Given the nature of OpenAI, I saw more focus on practical risks (hate speech, abuse, manipulating political biases, crafting bio-weapons, self-harm, prompt injection) than theoretical ones (intelligence explosion, power-seeking). That's not to say that nobody is working on the latter, there's definitely people focusing on the theoretical risks. But from my viewpoint, it's not the focus."

This paragraph doesn't make any sense. If you read a lot of Zvi or LessWrong, the misaligned intelligence explosion is the safety risk you're thinking of! So readers "guesses" are actually right that OpenAI isn't really following Sam Altman's:

"Development of superhuman machine intelligence is probably the greatest threat to the continued existence of humanity. There are other threats that I think are more certain to happen (for example, an engineered virus with a long incubation period and a high mortality rate) but are unlikely to destroy every human in the universe in the way that SMI could."[0]

[0] https://blog.samaltman.com/machine-intelligence-part-1

What a great post.

Some points that stood out to me:

- Progress is iterative and driven by a seemingly bottom up, meritocratic approach. Not a top down master plan. Essentially, good ideas can come from anywhere and leaders are promoted based on execution and quality of ideas, not political skill.

- People seem empowered to build things without asking permission there, which seems like it leads to multiple parallel projects with the promising ones gaining resources.

- People there have good intentions. Despite public criticism, they are genuinely trying to do the right thing and navigate the immense responsibility they hold.

- Product is deeply influenced by public sentiment, or more bluntly, the company "runs on twitter vibes."

- The sheer cost of GPUs changes everything. It is the single factor shaping financial and engineering priorities. The expense for computing power is so immense that it makes almost every other infrastructure cost a "rounding error."

- I liked the take of the path to AGI being framed as a three horse race between OpenAI (consumer product DNA), Anthropic (business/enterprise DNA), and Google (infrastructure/data DNA), with each organisation's unique culture shaping its approach to AGI.

> giant python monolith

this does not sound fun lol

> The thing that I appreciate most is that the company is that it "walks the walk" in terms of distributing the benefits of AI. Cutting edge models aren't reserved for some enterprise-grade tier with an annual agreement. Anybody in the world can jump onto ChatGPT and get an answer, even if they aren't logged in. There's an API you can sign up and use–and most of the models (even if SOTA or proprietary) tend to quickly make it into the API for startups to use.

The comparison here should clearly be with the other frontier model providers: Anthropic, Google, and potentially Deepseek and xAI.

Comparing them gives the exact opposite conclusion - OpenAI is the only model provider that gates API access to their frontier models behind draconic identity verification (also, Worldcoin anyone?). Anthropic and Google do not do this.

OpenAI hides their model's CoT (inference-time compute, thinking). Anthropic to this day shows their CoT on all of their models.

Making it pretty obvious this is just someone patting themselves on the back and doing some marketing.

It is fairly rare to see an ex-employee put a positive spin on their work experience.

I don't think this makes OpenAI special. It's just a good reminder that the overwhelming majority of "why I left" posts are basically trying to justify why a person wasn't a good fit for an organization by blaming it squarely on the organization.

Look at it this way: the flip side of "incredibly bottoms-up" from this article is that there are people who feel rudderless because there is no roadmap or a thing carved out for them to own. Similarly, the flip side of "strong bias to action" and "changes direction on a dime" is that everything is chaotic and there's no consistent vision from the executives.

This cracked me up a bit, though: "As often as OpenAI is maligned in the press, everyone I met there is actually trying to do the right thing" - yes! That's true at almost every company that ends up making morally questionable decisions! There's no Bond villain at the helm. It's good people rationalizing things. It goes like this: we're the good guys. If we were evil, we could be doing things so much worse than X! Sure, some might object to X, but they miss the big picture: X is going to indirectly benefit the society because we're going to put the resulting money and power to good use. Without us, you could have the bad guys doing X instead!

> It goes like this: we're the good guys. If we were evil, we could be doing things so much worse than X! Sure, some might object to X, but they miss the big picture: X is going to indirectly benefit the society because we're going to put the resulting money and power to good use. Without us, you could have the bad guys doing X instead!

This is a great insight. But if we think a bit deeper about why that happens, I land on because there is nobody forcing anyone to do the right thing. Our governments and laws are geared more towards preventing people from doing the wrong thing, which of course can only be identified once someone has done the wrong thing and we can see the consequences and prove that it was indeed the wrong thing. Sometimes we fail to even do that.

> everyone I met there is actually trying to do the right thing

making human beings obsolete is not the right thing. nobody in openAI is doing the right thing.

in another part of the post he says safety teams work primarily on making sure the models dont say anything racist as well as limiting helpful tips on building weapons of terror… and that AGI safety is basically not a focus. i dont think this company should be allowed to exist. they dont have ANY right to threaten the existence and wellbeing of me and my kids!

seems like the whole thing was meant to be a jab at Meta
This is a politically correct farewell letter. Obviously something we little people who need jobs have to resort to so the next HR manager doesn't think we are a risk to stock valuation. For a deeper understanding, read Empire of AI by Karen Hao. She defrocks Sam Altman to reveal he is just another human. Like Steve Jobs, he is an adept salesman appealing to the naïve altruistic sentiments of humans while maintaining his singular focus on scale. Not so different from the archetype of Rockefeller in his pursuit of monopoly through scale using any means, sam is no different than google which even forgot its own rallying cry ‘dont be evil’. Other actors in the story seem to have been infected by the same meme virus, leaving openAI for their own empires- Musk left after he and altman conflicted over who would be CEO.(birth of xAI). Amodei, his sister and others left to start anthropic. Sutskever left to start ‘safe something or other’(smacks of the same misdirection sam used when openAI formed as a nonprofit ) giving the idea of a nonprofit a mantle of evil since OPENAI has pivoted to profit.

The bottom line is that scaling requires money and the only way to get that in the private sector is to lure those with money with the temptation they can multiply their wealth.

Things could have been different in a world before financial engineers bankrupted the US (the crises of enron, salomon bros, 2008 mortgage debacle all added hundreds of billions to us debt as the govt bought the ‘too big to fail’ kool-aid and bailed out wall street by indenturing main street). Now 1/4 of our budget is simply interest payment on this debt. There is no room for govt spending on a moonshot like AI. This environment in 1960 would have killed Kennedy’s inspirational moonshot of going to the moon while it was still an idea in his head in his post coital bliss with Marilyn at his side.

Today our govt needs money just like all the other scrooge-infected players in the tower of debt that capitalism has built.

Ironically it seems china has a better chance now. It seems its release of deep seek and the full set of parameters is giving it a veneer of altruistic benevolence that is slightly more believable than what we see here in the west. China may win simply on thermodynamic grounds. Training and research in DL consumes terawatt hours and hundreds of thousands of chips. Not only are the US models on older architectures (10-100x more energy inefficient) but the ‘competition’ of multiple players in the US multiplies the energy requirements.

Would govt oversight have been a good thing? Imagine if General Motors, westinghouse, bell labs, and ford competed in 1940 each with their own manhattan project to develop nuclear weapons ? Would the proliferation of nuclear have resulted in human extinction by now?

Will AI’s contribution to global warming be just as toxic global thermonuclear war?

These are the questions that come to mind after Hao’s historic summary.

He joins a proven unicorn at its inflection point and then leaves mere days after hitting his vesting cliff. All of this "learning" and "experience" talk is sopping wet with cynicism.
„the right people can make magic happen“

:-)

> There's a corollary here–most research gets done by nerd-sniping a researcher into a particular problem. If something is considered boring or 'solved', it probably won't get worked on.

This is a very interesting nugget, and if accurate this could become their Achilles heel.

this post was such a brilliant read. to read about how they still have a YC-style startup culture, are meritocratic, and people get to work on things they find interesting.

as an early stage founder, i worry about the following a lot.

- changing directions fast when i lose conviction - things breaking in production - and about speed, or the lack of it

I learned to actually not worry about the first two.

But if OpenAI shipped Codex in 7 weeks, small startups have lost the speed advantage they had. Big reminder to figure out better ways to solve for speed.

>Safety is actually more of a thing than you might guess

Considering all the people who led the different safety teams have left or been fired, Superalignment has been a total bust and the various accounts from other employees about the lack of support for safety work I find this statement incredibly out of touch and borderline intentionally misleading.