x3haloed

OK, I like this in concept a LOT. I especially like that it's efficient and headless with an attachable GUI.

But I don't like how opinionated it is: "Therefore Prospero prime design principle: Never wait forever. Every operation has a deadline. This decision influences everything."

I respect that opinion, but I don't share it, and therefore an entire coding harness developed around that opinion is not helpful for me.

Oh, you are 100% correct about that.

I have a suspicion that eventually you won't have to be a developer to successfully create good software. I do think that familiarity with algorithm design will still help a lot. But ultimately, if your verification, testing, and observability regimes are good enough, the exact implementation shouldn't matter.

This is why, to me, it's more interesting to ask the question "how are good devs attaining outsized successes with AI" than "why are good developers wary of AI?"

Yes, there are real reasons to be careful, but that's already obvious to everyone in the field. The real gold is in discovering how successful devs are managing these risks while also retaining the benefits.

Honestly, I see good points in both of your comment sets.

But there really is a floor on how deeply a person can understand their own software. There has to be a "good enough" somewhere. As a C# dev, I can understand my entire codebase pretty deeply. And I've read enough of the .NET Core framework to understand some of the nuances of how a lot of the methods we rely on every day are implemented. But I've never once looked at the CIL that Roslyn has produced, and certainly not inspected the machine code that the runtime has compiled. I can't read or write Assembly. I don't really know anything about the x86 or ARM instruction sets. My understanding of the CPU is barely better than "it's transistors," and even lower than that, I have a vague awareness that neutrinos from space can flip bits and there are error correcting mechanisms for that, but I have no idea how they work. And yet, I'm able to write fast and reliable software.

There are super knowledgeable devs out there who pretty much DO understand the whole thing, but it's impossible to memorize every line of every version of framework that you're using or the unique alterations and upgrades to every piece of silicon that your program will run on, and as you guys pointed out, proprietary operating systems are basically completely opaque to our understanding.

So the question is really "where is the practical floor that you stand on?" And for me, personally, there is room for at least some areas of code at the application level that I'm OK with never having read myself.

I think this blog post is underbaked. I think it misplaces where the tension is, and also the skiing metaphor is attempting to simplify an explanation that's already simple.

The post describes the tension as being between leaders and developers. I don't really think that's where the tension is. I'm on a small team of all senior devs, and I've seen both sides -- skepticism and full embrace, and leadership was not pushing AI on us at all. On our team, no matter where we're each individually at on adoption, we're all pretty clear-eyed about the upsides and downsides. The upside is absurdly fast code production. The downside is losing touch with every line of code in the codebase.

There's no need to introduce the skiing metaphor, because the problem is simple: it's the devs' necks on the line when the system goes down or a customer record goes missing. When you get a call at 4 in the morning from the CEO, "Let me ask someone (AI)" isn't an acceptable answer. It's your job to know the failure modes like the back of your hand and be able to diagnose and rightsize in minutes. We've spent our whole careers guarding against those failures by agonizing over every line of code that goes into the product. With that understanding, it's pretty obvious why senior devs are hesitant to adopt something new without a clear picture of how they can be sure that the program isn't going to go down under load, isn't going to drop or mangle customer records, and when one of those things inevitably does happen, how to recover quickly. In a nutshell, job #1 for a senior dev is to account for every failure, and this becomes much harder when an automated system is pushing through 10x as much code.

I'm one of the devs who has chosen to adopt AI. As I reflect on that, I think the reason I'm willing to do so is because I have a level of certainty that I can work the pipeline to safely introduce more changes, faster. So far, I am getting mixed results, but that's not deterring me from continuing to try to reach an optimal point on the tradeoff curve.

This topic is bringing out the hallucination-panic crowd.

It's perfectly safe to use LLMs to surface underlying data and knowledge without having to trust that it's giving you correct advice.

Use the LLM as search technology: string match -> semantic search -> search intelligence.

This is especially helpful when you don't know the right question to ask. Semantics only help you find text that is semantically near the input query. Semantics won't help you when what you are looking for is connected to what you have by something other than semantics, like causation, mechanism, or interpretation.

Trying to figure out why your crops aren't growing well will likely require you to read several articles across a range of sciences, probably scoped to the specific conditions you are dealing with. A semantic search is not going to surface those first.

Allowing an LLM to chain together several sources for you to read first does not require you to ask it for a conclusion.

I'm curious why it's so upsetting to you. What does the existence of this repo represent to you that you hate?

I'd love to hear the story behind this. Motivation, methodology, alternatives considered, etc.

I generally agree with the diagnosis here, but:

> That isn’t a revolution.

What do you think a revolution is? Revolutions are literally complete upheavals of the system. The problem that you're really identifying is that this revolution appears to be unanticipated by the players fomenting it, and it also seems to be unintentionally targeted directly at themselves.

Wherever this goes, it's sure to be interesting.

Maor dots!! Does anyone have their dots yet?

If OP sees this, I really like how you are thinking about things. It's really hard to see forward. The target isn't fixed. Bell Labs, Apple, etc. were mostly solving for a fixed target. But now the target is a relationship between humans and LLMs, and the way that LLMs work has been evolving rapidly. I can think of a number of ways to conceptualize how things are moving, but they're probably all wrong. My best guesses about what needs to remain stable is that I don't think shared software is going away entirely, and I don't think all input is going to collapse to just a microphone and a camera. There is a floor on tasks that we want agents to do for us. I'd rather rename a file on my desktop or text my friend myself. Apple and Google have both tried very hard to abstract the file away from user reach, but it's such a convenient unit of sharing, that it might stick around for a while.

I love PocketTTS. It's stupid fast and the voice quality is decent. But it's not the highest quality.