For context:

We went from “cannot understand the difference between C and PHP” to “can sometimes write a valid function” to “works reasonably well to work on single files” to “can build a full greenfield app but needs extensive guidance on architecture and APIs” to “can build a full app with an engineer in the loop and build on top of it for a few weeks” to “decent at architecture and can build smaller systems without guidance” in 3 years.

But when I was trying to talk about labor issues and it being a paradigm shift for the industry at large, the standard response was that I was deluded and spreading FUD. The take that the tools are useless has been constant too, except the goal posts constantly move to whatever the current state of the art. Another take that never dies is that using llm based tools somehow can’t involve skill, that there is no difference between the prompting of an experienced software engineer who has spent years working with llms and the 3 prompts one has put into a random model “to try things out”. Imagine someone coming to like Elixir from Java, typing a few classes in Java, runs it and gets errors and say “elixir is kinda useless, all I got to run was this super barebones program after 17 tries and lots of compile errors”.

Whether one like using these tools or not (especially if you don’t like them), and especially if you are relatively new to them, spend just a few minutes or hours to compare how far you get with llama (the OG) and pure copy paste by hand, to a newer 8B model in an agent harness, to a model like glm5.1 to gpt5.5 or opus4.6 in a harness.

That’s the last 2 years in a bottle.

#llm #llms #genai #claude #vibecoding