Comments URL: https://news.ycombinator.com/item?id=48524772

Points: 2

# Comments: 0

Sounds a lot like vibe coding lol

Thanks, but no thanks!

Most of the “impressive” stuff is not “the model” but “the harness”. Spinning up the subagents and teams of lower models, letting them explore, do adversarial coding. It’s all in the harness. Granted, Mythos might be better at that orchestration, but it’s still the harness.

Second is the prompting. The author is an expert in what they’re doing and prompts the system in a way that yields useful results. I see too many people believing that if an expert can achieve those results in a domain they’re familiar with, then them as non-experts will be able to as well. And that’s a fallacy that Mythos doesn’t change.

So, for context, two data points I have that make me want to argue for the opposite side.

First, some time ago I worked for a startup that had a B2B offering that in most cases involved integration costs to align with whatever the client was already using. We tried to eat this as much as possible, but we still had to have some “integration price” we asked. More than once we had a potential client who just couldn’t lift it. They needed the software but just didn’t have the cash buffer for the initial cost (us neither). With how things are now, we’d have onboarded all of them. And much faster than it normally took. And yes, they still would have bought our solution instead of rolling their own (see the next point).

The next point that kind of ties into the previous one if you squint. I’m in a position now where I see non-technical people building stuff with AI. _Most_ can’t. As an example, the AI says they need a database. But they don’t really know what that is, and deploying one sounds scary, so they ask the AI if they can build it without a database. And the AI happily complies and makes a “CRUD” API that “persists” data in RAM. And the AI is not being dumb here. The best, most perfect model is still an LLM at the end of the day, so it completes the context window. Sure, you could make a mod that “sticks to its guns” more, but that comes across as the model being “non-compliant” and “difficult”. Now, I’ve also seen non-technical people who have succeeded. But then they have the kind of a mindset that they could’ve been engineers in the first place in different circumstances. But also, even they build fragile monstrosities that they don’t understand.

So, going back to the first point. Our clients were deeply nontechnical for the most part. Most of them wouldn’t even have attempted to build their own. But also, getting the system up and working involved more than just code - relationships with suppliers, some legal stuff, etc.

So, I can totally see how the amount of software produced might grow exponentially leading to “pre-AI” engineers being worth their weight in gold due to that. That doesn’t exclude a painful transition though.

I don’t think the data really supports this? Last I checked at least.

Comments URL: https://news.ycombinator.com/item?id=48320007

Points: 14

# Comments: 4

Doesn’t work well ofc in a one shot situation with no context.