My favorite movie quote as it pertains to software engineering has for a long time been Jurassic Park's: “Your scientists were so preoccupied with whether or not they could, they didn’t stop to think if they should.”

That’s how I feel about a lot of AI-powered development. Just because you can have 10 parallel agents cranking out features 24/7 and have AI write 100% of the code, that doesn’t mean you’re actually building a product that users want and/or that is a viable business.

I’m currently in this situation, working on a greenfield project as founder/solo dev. Yes, AI has been tremendously useful in speeding things up, especially in patching over smaller knowledge gaps of mine.

But in the end, as in all the projects before in my career, building the MVP has rarely been the hard part of starting a company.

In my experience with a combo of Claude Code and Gemini Pro (and having added Codex to the mix about a week ago as well), it matters less whether it’s CLI, backend, frontend, DB queries, etc. but more how cookiecutter the thing you’re building is. For building CRUD views or common web application flows, it crushes it, especially if you can point it to a folder and just tell it to do more of the same, adapted to a new use case.

But yes, the more specific you get and the more moving pieces you have, the more you need to break things down into baby steps. If you don’t just need it to make A work, but to make it work together with B and C. Especially given how eager Claude is to find cheap workarounds and escape hatches, botching things together in any way seemingly to please the prompter as fast as possible.

I'm not against AI art per se, but at least so far, most “AI artists” I see online seem to care very little about the artistry of what they’re doing, and much much more about selling their stuff.

Among the traditional artists I follow, maybe 1 out of 10 posts is directly about selling something. With AI artists, it’s more like 9 out of 10.

It might take a while for all the grifters to realize that making a living from creative work is very hard before more genuinely interesting AI art starts to surface eventually. I started following a few because I liked an image that showed up in my feed, but quickly unfollowed after being hit with a daily barrage of NFT promotions.

Do you think that for someone who only needs careful, methodical identification of “problems” occasionally, like a couple of times per day, the $20/month plan gets you anywhere, or do you need the $200 plan just to get access to this?

I've had the $20/month plan for a few months alongside a max subscription to Claude; the cheap codex plan goes a really long way. I use it a few times a day for debugging, finding bugs, and reviewing my work. I've ran out of usage a couple of times, but only when I lean on it way more than I should.

I only ever use it on the high reasoning mode, for what it's worth. I'm sure it's even less of a problem if you turn it down.

$200 on claude for vibe coding, $20 on codex for code review and "brainstorming". I use other LLM for a 2nd - 3rd - 4th opinion.

The $20 does this fine.

The OpenAI token limits seem more generous than the Anthropic ones too.

Listening to Dario at the NYT DealBook summit, and reading between the lines a bit, it seems like he is basically saying Anthropic is trying to be a reponsible, sustainable business and charging customers accordingly, and insinuating that OpenAI is being much more reckless, financially.

I think it's difficult to estimate how profitable both are - depends too much on usage and that varies so much.

I think it is widely accepted that Anthropic is doing very well in enterprise adoption of Claude Code.

In most of those cases that is paid via API key not by subscription so the business model works differently - it doesn't rely on low usage users subsidizing high usage users.

OTOH OpenAI is way ahead on consumer usage - which also includes Codex even if most consumers don't use it.

I don't think it matters - just make use of the best model at the best price. At the moment Codex 5.2 seems best at the mid-price range, while Opus seems slightly stronger than Codex Max (but too expensive to use for many things).

Consumer subscriptions are an impossible business, that's why openai NEEDS ads to have any chance of sustainability.

I use it everyday and the $20 plan is fine

I would argue that many engineering “best practices” have become much more important much earlier in projects. Personally, I can deal with a lot of jank and lack of documentation in a early stage codebase, but LLMs get lost so quickly, or they just multiply the jank faster than anyone ever could have in the past, making it much, much worse for both LLMs and humans.

Documentation, variable naming, automated tests, specs, type checks, linting. Anything the agent can bang its proverbial head against in a loop for a while without involving you every step of the way.

I don't think Google is bad at building products. They definitely are excellent at scaling products.

But I reckon part of the sentiment stems from many of the more famous Google products being acquisitions orignally (Android, YouTube, Maps, Docs, Sheets, DeepMind) or originally built by individual contributors internally (Gmail).

Then here were also several times where Google came out with multiple different products with similar names replacing each other. Like when they had I don't know how many variants of chat and meeting apps replacing each other in a short period of time. And now the same thing with all the different confusing Gemini offerings. Which leads to the impression that they don't know what they are doing product wise.

Starting with an acquisition is a cheap way of accelerating once your company reaches a certain size.

Look at Microsoft - Powerpoint was an acquisition. They bought most of the team that designed and built Windows NT from DEC. Frontpage was an acquisition, Azure came after AWS and was led by a series of people brought in in acquisitions (Ray Ozzie, Mark Russinovich, etc.). It's how things happen when you're that big.

I think it's a little unfair to give DEC credit for NT. Sure, they may have bought the team, but they did most (all?) of the work on NT at Microsoft.

That's not like Google buying Android when they already had a functioning (albeit not at all polished) smartphone OS.

Why wouldn't you count things initially made by individual contributors at Google?

Because those were "free time" projects. It wasn't directed to do by the company, somebody at the company with their flex time - just thought it was a good idea and did it. Googlers don't get this benefit any more for some reason.

Because they're not a good measure of the company's ability to develop products based on the direction from leadership.

Leadership's direction at the time was to use 20% of your time in unstructured exploration and cool ideas like that, though good point of the other poster that that is no longer a policy.

I switched away from Spotify a couple of years ago because of this, after having been a paying customer for around 10 years.

But I fear all such services will eventually succumb to this, given just how much more lucrative ads can be compared to subscriptions.

I did the same, and switched to Apple Music. Soon after that, Apple Music started injecting their F1 movie soundtrack into suggested music for me. There really is no escape from this. They haven't done it since, so at least it's not as bad as what Spotify does. If I come across a good offline music player for iOS I will probably cancel my Apple Music subscription.

Is suggested music not already an ad? Why not just listen to your library?

That's not an ad and sounds like a you problem. I've never had the F1 soundtrack being played on radio/random and I do listen to a lot of soundtracks.

Last time I checked the sky tv financials, subscription revenue outweighed advertising revenue about 10:1, is for every £30 subscription they took £3 in adverts.

I agree that people shouldn’t rely solely on AI to decide how to vote.

Unfortunately, given the sorry state of the internet, wrecked by algorithms and people gaming them, I wouldn’t be surprised if AI answers were on average no more or even less biased than what people find through quick Google searches or see on their social media feeds. At least on the basics of a given topic.

The problem is not AI, but that it takes quite a bit of effort to make informed decisions in life.

In my opinion, if those influential programmers actually architected around some concrete metrics like 1,000 TPS and 10K daily users, they would end up with much simpler systems.

The problem I see is much more about extremely vague notions of scalability, trends, best practices, clean code, and so on. For example we need Kafka, because Kafka is for the big boys like us. Not because the alternatives couldn’t handle the actual numbers.

CV-driven development is a much bigger issue than people picking overly ambitious target numbers.

I’d argue that those kinds of automated tools are much more important much earlier in a project than they used to be.

Personally, I can deal with quite a lot of jank and a lack of tests or other quality control tools in the early stages, but LLMs get lost so quickly. It’s like onboarding someone new to the codebase every hour or so.

You want to put them into a feedback loop with something or someone that isn’t you.