> Does "career development" just mean "more money"?
Big companies means more opportunities to lead bugger project. At a big company, it’s not uncommon to in-house what would’ve been an entire startup’s product. And depending on the environment, you may work on several of those project over the course of a few years. Or if you want to try your hand at leading bigger teams, that’s usually easier to find in a big company.
> Is it still satisfying if that software is bad, or harms many of those people?
There’s nothing inherently good about startups and small companies. The good or bad is case-by-case.
My experience at big companies has been that you only get the opportunity to do something big if you are willing to waste years "proving yourself" on a lot of tedious bullshit first. The job you want is not the job you get to apply for, and I've never had the patience to stick it out. Smaller companies let me do meaningful work right away.
Politely, I disagree. It means you are in a context where the risk aversion is high, everyone keeps their head down.
Done right, you can be a disruptor, for what are very benign or proven changes outside of the false ecosystem you are in.
I recommend these changes are on the level of "we will allow users to configure a most used external tool on a core object, using a URI template" - the shock, awe, destruction is everyone realizing something is a web app and you could just... If you wanted... Use basic HTML to make lives better.
Your opponents are then arguing against how the web works, and you have won the framing with every employee that has ever done something basic with a browser.
You might find this level of "innovation" silly, but it's also representative of working in the last few tiers of a distribution curve - the enterprise adopters lagging behind the late adopters.
> Big companies means more opportunities to lead bugger project. At a big company, it’s not uncommon to in-house what would’ve been an entire startup’s product. And depending on the environment, you may work on several of those project over the course of a few years. Or if you want to try your hand at leading bigger teams, that’s usually easier to find in a big company.
Okay, so career development means "bigger projects"?
> There’s nothing inherently good about startups and small companies. The good or bad is case-by-case.
Well, maybe not, but I think the post illustrates some ways big companies are worse. I'd say that, all else being equal, companies tend to get bigger by becoming more doggedly focused on money, which tends to lead to doing evil things because you no longer see refraining from doing so as important compared to making money. Also, all else equal, a company that does something bad on a small scale is likely less bad than one that does something bad on a large scale.
projects beyond a certain size in a large org imply things which are very different - people, networking, money, regulations, politics, business, security etc all things which don’t look spectacular when you have three people, but become very important and much harder with hundreds of people.
So career development really means ‘learning a completely different skillset which is not technical’
That's a good way to put it and is something I've often thought as well, although not just in the technical realm. I think of it as "doing a different job". You used to be a teacher but now you're the principal; you used to hammer in nails but now you direct the construction crew; you used to be writing software but now you manage other people who write software; etc.
Personally I'd struggle to consider that "development" for my own life, since it often amounts to no longer doing the job I like and instead watching other people do it. I can understand how adding new skills is positive, though.
This can be mitigated by learning other technical fields ( infrastructure, security, etc ) and using your technical knowledge to steer things in the right direction - but yes, you’re otherwise right and I understand your point of view.
GPT-4 is very different from the latest GPT-4o in tone. Users are not asking for the direct no-fluff GPT-4. They want the GPT-4o that praises you for being brilliant, then claims it will be “brutally honest” before stating some mundane take.
It feels crazy to keep arguing about LLMs being able to do this or that, but not mention the specific model? The post author only mentions the IMO gold-medal model. And your post could be about anything. Am I to believe that the two of you are talking about the same thing? This discussion is not useful if that’s not the case.
The 5 seconds delay is probably due to reasoning. Maybe try setting it to minimal? If your use case isn’t complex maybe reasoning is overkill and gpt-4.1 would suffice.
o3 is the best OpenAI model but it still makes tons of mistakes. It's got a very strong background in most of undergrad level math, and a decent amount of grad level machine learning stuff, but its tendency to hallucinate means it will greedily fixate on some initial conjecture early on, not realize it's a conjecture, and continue to assert that it's true for the rest of the conversation. Similarly, if it thinks something is impossible, it will just assert that and continue to assert again and again that it's impossible, even if it's actually true. It's like the mathematical version of a hallucination. There is no real reason it should do this for grad level topics - they just haven't trained it enough. It has a survey level knowledge of a TON of ideas, which can be great if you are looking for topics related to something, but as far as the details of exactly how things are related, what subtleties and caveats there are and so on, it will just hallucinate its first guess and get stuck there for the rest of the conversation.
o3-pro is maybe marginally better, but it takes a very long time to respond and so I rarely use it.
4o is much worse and so I usually use o3.
Gemini 2.5 Pro is much better - and free. Grok 4 is also probably up there with Gemini 2.5. They just have less tendency to hallucinate in this way in general: they will spend more time reasoning, checking claims, searching for prior literature, etc. They still mess up, but not quite as much as o3. I don't use Sonnet or Opus for math all that much - my impression was that o3 was better than Sonnet 3.7 but not sure about 4.
I asked 04-mini how many prime numbers are divisible by 35 with a remainder of 6. It confidently stated that there are 'none'. It hadn't even tried hard enough to get to 41.
