I think there's aspects of this viewpoint that are true. I'm sure I'm less skilled at programming now in some ways than when I started using LLMs, but I'm a lot more productive and I can work on a broader variety of software than I could before. Writing probably weakened people's auditory memory, and calculators probably reduced people's mental math skills, but I don't think either are a net negative. It just requires some adjustment to get used to the new way things are. I also think my programming skills would come back pretty quick if I started programming without LLMs again, just as my leetcode skills come back pretty quick when I prepare for interviews.
I feel like LLMs have been nothing but a boon for me. I have learned so much programming from them. I have over a decade of experience, but honestly, I have always been a below-average programmer. Good enough for boring CRUD work, but not much more. Forget Leetcode, I'd probably get murdered on the easy questions.
So, if anything, I feel like my learning pace has been greatly accelerated. Your point about working on a broader variety of software is really true for me too. I am working on a game that I likely would have never even started had it not been for LLMs. Mind you, I am still doing the vast majority by hand. However, LLMs have been great for little tutorials, setting out a good game plan, etc. It's like having my own little private tutor.
I know enough to not let the LLMs do everything for me. If they do, then I know I will fall into the trap of something breaking, and then I lack the understanding to fix it. I think they should be used to make life easier, but not easy.
I rarely use image search, but I went to look something up recently and I was shocked at how many obviously AI generated images showed up. I couldn't even find an image of the thing I was looking for and eventually gave up. Bing has the same problem.
There's a trend in top MBA programs called entrepreneurship through acquisition (ETA) where you raise money to buy a business that you acquire through a mixture of debt and equity. Basically lets MBAs skip the building phase of building a small business and go right into operating it.
I run a small business on the side, and although I did a ton of preparatory reading and learning not much of it was useful in retrospect. Most of it you learn by doing and it's not that hard to learn. The top three things that were useful to me to learn were sales, basic accounting and how to read financial statements, and what metrics to track/manage with. You can learn the basics for all of those in less than a month.
My advice is just start. You are probably wrong about what the market wants unless you are selling a product or service that you know there is already demand for. Figure out what it is you're offering and try selling it to people. If they want it you figure out how to make it better, if they don't you try something else.
Edit: I had wanted to start a business for a long time. I thought I needed some tricky new idea to be successful. That's really hard to come up with since most new ideas are bad or are too hard to sell/explain to people. In my case it was also a form of procrastination since I had to wait for the right idea. Things got easier when I just picked an existing problem/industry and decided to do that with my own proprietary software to make it easier for me. I know a guy making a couple million a year from owning multiple tanning salons. There's a lot of opportunity out there that doesn't require any special insight.
I completely agree. From my experience in Academia, what happens is, that university departments simply don't know better. They scramble together a course or program they think its needed, and shape it from THEIR perspective of what it should include.
Its like now, when every SaaS company scrambles a way to put AI into their product, just because they think they need to.
I guess one thing universities have to decide is how important having founders is to them. PG talks about how Harvard has more founders than Yale and Princeton, but I don't really see that as a good or bad thing for any of those schools. There probably aren't infinite good ideas that can be successful at any one time. If you encourage more people to become founders then they aren't going to go into other places where their skills might be better suited.
YC's founders also skew heavily towards a certain type of person and business. The returns of VC in biotech for example are much lower than the returns in B2C and B2B software. It's just a harder, more capital intensive, and more uncertain industry. Over optimizing for the YC archetype means you get less of the people who succeed in other areas.
Also, although PG disdains finance and management, many large problems are better addressed through people with skills in these areas IMO, since often the returns are not sufficient to attract VC interest but the financial and human resources that need to be coordinated to address them are substantially beyond the ability of a small, undercapitalized group.
"There probably aren't infinite good ideas that can be successful at any one time. If you encourage more people to become founders then they aren't going to go into other places where their skills might be better suited."
Yes, exactly. I do not think you need to try so hard to get more founders. Most small businesses fail. And even most venture-backed startups fail. You are already throwing a ton of eggs at the wall, which is mostly a waste of eggs. Even one of YC's largest successes (DoorDash) is nothing but a middle man of fast food enabled by mobile technology, which it did nothing to invent.
Anecdotally, I think there are more rich children at Harvard than Yale (more legacies, more donations to get their child in, etc). Those people have more time to take a risk as a founder than non-wealthy.
Other way around from personal experience. Harvard is louder because Harvard and alums from middle class backgrounds like I beat the drum.
Harvard has also offered non-traditional open-entry bachelor degrees for over a century and whose endowment became the precursor for WGBH and therefore PBS, and those of us from other schools don't treat them any different. The only other ivies with large dedicated non-trad programs are Columbia (Asimov was a product of that) and Penn.
Yale, Dartmouth, and to a lesser extent Princeton is blue blood af.
> Also, although PG disdains finance and management, many large problems are better addressed through people with skills in these areas IMO
I find this view from pg very narrow minded, and borderline ignorant. He is shaping his essay as in the role of higher education and academia is only to produce startup founders. Which is not, it is a way of a state investing into a labor force that is needed. As long as there are large corporate multinationals, there will be a need for finance, economics and yes, even management. Are a lot of that studies fugazi? Sure they are, but so are a lot of startups.
If everyone coming out of academia would be startup-like, corporations and other businesses simply wouldnt have the workforce for their machinery, and then some big shoot CEO would write blogs how Universities Should Prepare White Collars.
And indeed, reading period produced two trillion dollar companies, but this is statistical anomaly. You could just as well argue, that it keps economy afloat by educating up-coming workforce, but thats harder to prove.
There are so many VC's and so much money today the demand for "Founders" is high. One way to increase supply is to manufacture what you need - much like Korean K-Pop bands. Band members start in a Bootcamp. They learn to dance and get a vocal coach. As their fan base grows they start to disrupt and displace older bands that are aging out. The industry as a whole does well but individual band may or may not. Do they produce new and innovative music? - meh. Let's face it - a "Founder" with the right fan base can get valuations over a trillion:)
I do think it is kind of funny when VCs talk about how they can tell who will be a successful founder. They are picking the people who get to call themselves founders so it is close to tautological that who they think will be successful matches who ends up succeeding. You don't get to see the counterfactual world where the non-funded people get given money and then you see what personality distribution the successes from that group have. The problem probably is worse now since there are fewer IPOs and more companies exit in private transactions where it's not clear how much economic value was actually created vs how much is just what the investors agree the business is worth.
When I originally started in this business it was truly exciting. VC's where the only place to go to fund truly unique companies and products that were highly risky. Disruption was often a byproduct not a goal. The goal now - collect as big a war chest as you can - disrupt something that already exist and may even be working well - own it all because you have the biggest war chest and can.
It makes organizations more productive at producing code and doing other tasks, but translating that into something that affects PnL is different. Where I work it's sped up individual tasks I've worked on but I don't think it's sped up delivery timelines of any of the major projects I'm involved in. We just added additional verification work with the extra cycles the engineers have now. It's not like that work is useless. It will probably mean I have less debugging to do in the future, but when you look at how the business makes money I don't see it making a big impact.
I think it is easy for companies to waste time and money on lots of things when it is hard to measure the impact. For example, I think most people would agree that the big tech companies are bloated and have too many employees for the amount of work they have. There's not really an incentive to fix problems, and in some cases (like with headcount) there are counter-incentives (managers want to have more reports).
I think companies will get better at measuring the impact of AI and attributing it to increasing profit or decreasing costs, and that the companies that are better at this will have an advantage over those that are worse, so eventually overall efficiency will improve.
No, it's been my experience asking LLMs to explain complicated code to me. They can do a pretty good job of it. You can also ask them to write a bunch of tests and then rip out the old implementation and fix it with a new one. LLMs aren't perfect but they are really good at understanding and writing code.
It depends on what one's idea of an implementation is and what one's expectations are.
If an implementation is "a black box that works," absolutely, LLMs are fine. They can create complex programs in full.
But if one expects a tight implementation... it's a horror. LLMs vastly overengineer code (I believe they're intentionally designed to do so). I really struggle to make LLMs generate lean code.
In the best case, they generate bloated designs (in terms of complexity, not necessarily performance), but in the worst case, they generate gaps in the specification. And even in the first case - cognitive load is a problem also for LLMs, not just for humans (although obviously at a larger scale).
I think LLMs are essentially modern compilers, with similar problems, but designed more like "deoptimizing compilers" than optimizing ones. :)
That's surprising to me. I recently switched from Claude to Codex because I was blowing through my Claude limits. With Codex I haven't been able to use up all of my usage on the 20x plan, with Claude and fable I could do that in a day. Codex is also a lot faster than Claude. I do think Fable is slightly better and can come up with better abstractions than Codex but trying to read it's output became really frustrating to me.
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