Absolutely—I feel like I can ship at a crazy velocity now, like I have a team of interns at my disposal to code up my every silly demand.
`Cut my eggs`
`Your eggs are cut sir!'
`Cut my milk'
`I can't sir, it's liquid'
`Imbecile! Freeze it, then cut it!'I also wonder what type of simple CRUD apps people build that have such a performance gain? They must be building well understood projects or be incredible slow developers for LLMs to have such an impact, as I cant relate to this at all.
In my experience, it seems the people who have bad results have been trying to get the AI to do the reasoning. I feel like if I do the reasoning, I can offload menial tasks to the AI, and little annoying things that would take one or two hours start to take a few minutes.
That very quickly adds up to some real savings.
Agents finish, I queue them up with new low hanging fruits, while I architect the much bigger tasks, then fire that off -> Review smaller tasks. It really is a dance, but flow is much easier achieved when I do get into it; hours really just melt together. The important thing to do is to put my phone away, and block all and any social media or sites I frequent, because its easy to get distracted when agents aren just producing code and you're sitting on the sidelines.
At my first job in Silicon Valley, I used to code right on the production floor totally oblivious to what was going on.
Can we see this frontend code? For research purposes, of course.
Good nugget. Effective prompting, aside from context curation, is about providing the LLM with an approximation of your world model and theory, not just a local task description. This includes all your unstated assumptions, interaction between system and world, open questions, edge cases, intents, best practices, and so on. Basically distill the shape of the problem from all possible perspectives, so there's an all-domain robustness to the understanding of what you want. A simple stream of thoughts in xml tags that you type out in a quasi-delirium over 2 minutes can be sufficient. I find this especially important with gpt-5, which is good at following instructions to the point of pedantry. Without it, the model can tunnel vision on a particular part of the task request.
I suspect it doesn't matter how we feel about it mind you. If it's going to happen it will, whether we enjoy the gains first or not.
* setting aside whether this is currently possible, or whether we're actually trading away more quality that we realise.
fearface•53m ago