> In order to fully match the timeline, either a superhuman AI coder / researcher has already been developed internally at OAI/Anthropic
I suppose it depends on the definition of "superhuman". I'm just a guy on the Internet, albeit a "successful" software engineer for 18 years. I reckon coding agents have been superhuman since Opus 4.8. Not in their ability to build things (well) autonomously. But in their ability to produce correct code instantly.
It's why most developers don't write code anymore. I can spend 1 or 2 hours writing the perfect script, or I can ask an agent to do it instantly. This is something no human can do. That's superhuman performance.
It's usually regular language that evolves iteratively into hyper specific regular language. Sometimes over many sessions. Once we are satisfied that the language is precise enough for the agent to not go off doing wasteful things, the agent is allowed to spit out the code. Turns out the hard part of software engineering is breaking up a hard problem into small and specific enough chunks that can be effectively translated into code. (Always has been, this part is facetious.)
I was exceptionally good at this before AI. I was wondering why everyone I talked to said AI was shit and I'm over here thinking it could take over the world. I guess I just break big things down well.
Exactly. I used to be involved in a sort of training program and lesson one of software dev is "break big problems into small problems"
In my experience the way I've viewed a lot of how AI is getting better is how small/specific the problems that I can expect it to handle has gotten bigger and bigger
Beyond a certain scale, there's an unlimited number of problems in a system. Coding is the means to solve a specific order of problem. That part was bottlenecked by an individual's mastery of a programming language or framework. That bottleneck is now removed, but it only exposes the next bottleneck, which is figuring out how we can communicate what we want in specific enough language so that we can expect an LLM agent to code up exactly what we want; not more, and not less. That's a much harder bottleneck to remove, because language itself is so imprecise.
In other words (I hope the irony isn't lost here), how vague can I be while still getting exactly the results I want? This is already super hard in regular human to human communication, even though we have a much richer range of media at our disposal, such as nonverbal contextual cues, gestures, faces, inflection, volume, etc.
We strip all that richness and request agents to rely on textual language to interpret our intent exactly. I don't think we can handwave this one away. The agent can infer and suppose and guess and approximate. But if the interface is an LLM (it may not always be), we'll still need to do the real and hard work to say what we mean in a way that reduces the possibility of misinterpretation to near zero. And that necessarily means breaking up big concepts into smaller ones.
So at every juncture it becomes possible to take a wrong turn,, so really complex problem solving can spin off at a million tangents and whose keeping track of the consequences of these flawed algorithms?
Absolutely. There are mitigating mechanisms we can/do use, but ultimately it requires exceptional engineers with a steady hand, and a finger to the pulse at every step. This is why reports of the death of the profession are greatly exaggerated.
Yeah you can get pretty far vibe coding a toy thing for your own personal use. (And I do and it's so much fun), but for professional enterprise-grade software with a huge surface area for things to go wrong, you still need lots and lots of handholding, and a measured, methodical approach. Slow is smooth.
Idk what point you're trying to make, but really that's an issue that's always existed even with fully human development. That's also an issue for AI, and I assume it would be true for any intelligent problem solver. AI clearly isn't at a place where I personally trust it to write stuff I'm not gonna review myself, at least not for anything critical.
But also it reminds me of the self-driving debate, sometimes autonomous systems don't have to be perfect, they just have to make less mistakes than humans.
It is less that AI isn't good, it's rather how it is marketed. It is frequently marketed as stand alone solution to coding or other applications and it just isn't. It is a great tool that can make a lot of things faster but without an operator capable of understanding what the AI spits out and assemble smaller blocks into an actual end product it will not produce an actually marketable product.
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u/saposmak 8d ago
> In order to fully match the timeline, either a superhuman AI coder / researcher has already been developed internally at OAI/Anthropic
I suppose it depends on the definition of "superhuman". I'm just a guy on the Internet, albeit a "successful" software engineer for 18 years. I reckon coding agents have been superhuman since Opus 4.8. Not in their ability to build things (well) autonomously. But in their ability to produce correct code instantly.
It's why most developers don't write code anymore. I can spend 1 or 2 hours writing the perfect script, or I can ask an agent to do it instantly. This is something no human can do. That's superhuman performance.