Comment by _pdp_
22 days ago
I was skeptical until 3-4 months ago, but my recent experience has been entirely different.
For context: we're the creators of ChatBotKit and have been deploying AI agents since the early days (about 2 years ago). These days, there's no doubt our systems are self-improving. I don't mean to hype this (judge for yourself from my skepticism on Reddit) but we're certainly at a stage where the code is writing the code, and the quality has increased dramatically. It didn't collapse as I was expecting.
What I don't know is why this is happening. Is it our experience, the architecture of our codebase, or just better models? The last one certainly plays a huge role, but there are also layers of foundation that now make everything easier. It's a framework, so adding new plugins is much easier than writing the whole framework from scratch.
What does this mean for hiring? It's painfully obvious to me that we can do more with less, and that's not what I was hoping for just a year ago. As someone who's been tinkering with technology and programming since age 12, I thought developers would morph into something else. But right now, I'm thinking that as systems advance, programming will become less of an issue—unless you want to rebuild things from scratch, but AI models can do that too, arguably faster and better.
It is hard to convey that kind of experience.
I am wondering if others are seeing it too.
I'm seeing it too, but there's a distinction I think matters: AI isn't replacing the thinking, it's shifting where the bottleneck is. You mention systems are self-improving and code quality has increased dramatically. But the constraint isn't execution anymore. It's judgment at scale. When AI collapses build time from weeks to hours, the new bottleneck becomes staying current with what's actually changing. You need to know what competitors shipped, what research dropped, what patterns are emerging across 50+ sources continuously. Generic ChatGPT can't do that. It doesn't know what YOU care about. It starts from scratch every time. The real question is how do you build personal AI that learns YOUR priorities and filters the noise? That's where the leverage is now.
Excited for the future :)
> You need to know what competitors shipped, what research dropped, what patterns are emerging across 50+ sources continuously. Generic ChatGPT can't do that.
You're saying that a pattern recognition tool that can access the web can't do all of this better than a human? This is quintessentially what they're good at.
> The real question is how do you build personal AI that learns YOUR priorities and filters the noise? That's where the leverage is now.
Sounds like another Markdown document—sorry, "skill"—to me.
It's interesting to see people praising this technology and enjoying this new "high-level" labor, without realizing that the goal of these companies is to replace all cognitive labor. I strongly doubt that they will actually succeed at that, and I don't even think they've managed to replace "low-level" labor, but pretending that some cognitive labor is safe in a world where they do succeed is wishful thinking.
If these agent are so great was isn't ChatBotKit a highly successfully public company worth hundreds of billions and not just a glorified chatgpt wrapper? If you're able to do so much with so little why isn't that actually bearing out in becoming a profitable company? What's the excuse?
Do people really need to know that a bunch of code at a company that won't exist in 10 years is something worth caring about?
Because we are not hyping to lure investors to give us hundreds of millions dollars. We took the more honest route and work with actual customers. If we are to accept hundreds of millions at some point perhaps we are going to reach hundreds of billions in valuation ... on paper.
As for the chatgpt wrapper comment - honestly this take is getting old. So what? You are going to train your own LLM and run it at huge loss for awhile?
And yes perhaps all of this effort is for nothing as it may be even possible to reacted everything we have done from scratch in a week assuming that we are static and do nothing about it. In 10 years the solution would have billions of lines of code. Not that lines of code is any kind of metric for success but you wont be able to recreate it without significant cost and upfront effort ... even with LLMs.
Agreed. I don’t know if it will create or eliminate jobs but this is certainly another level from what we’ve seen before.
Since last 2 months, calling LLMs even internet-level invention is underserving.
You can see the sentiment shift happening last months from all prominent experienced devs to.
Yeah, the latest wave of Opus 4.5, Codex 5.2, Gemini Pro 3 rendered a lot of my skepticism redundant as well. While I generally agree with the Jevon's paradox line of reasoning, I have to acknowledge it's difficult to make any reasonable prediction on technology that's moving at such immense speed.
I expected the LLM's would have hit a scaling wall by now, and I was wrong. Perhaps that'll still happen. If not, regardless of whether it'll ultimately create or eliminate more jobs, it'll destabilize the job market.
But still the hypothesis of the article holds stance. If you want a new feature, you still have to think it through and explain the AI how to implement it, and validate the result.
You might be able to do more with less, but that is with every technological advancement.
Regarding your experience, it sounds like your codebase is such good quality that it acts as a very clear prompt to the AI for it to understand the system and improve it.
But I imagine your codebase didn't get into this state all by itself.
My guess: projects "learn" every time we improve documentation, add static analysis, write tests, make the API's clearer, and so on. Once newly started agents onboard by reading AGENTS.md, they're a bit "smarter" than before.
Maybe there's a threshold where improvements become easy, depending on the LLM and the project?
As a hobbyist programmer, I feel like I've been promoted to pointy-haired boss.