This isn't a magic code genie, it's a very complicated and very powerful new tool that you need to practice using over time in order to get good results from.
you: HAVE YOU PUT MORE TOKENS IN???? ARE YOU PUTTING THEM IN THE EXPENSIVE MACHINES???
super compelling argument /s
if you want to provide working examples of "prompt engineering" or "context engineering" please do but "just keep paying until the behavior is impressive" isn't winning me as a customer
it's like putting out a demo program that absolutely sucks and promising that if I pay, it'll get good. why put out the shit demo and give me this impression, then, if it sucks?
Then it ran out of money again, and I gave it even more money.
I'm in the low 4 figures a year now, and it's worth it. For a day's pay each year, I've got a junior dev who is super fast, makes good suggestions, and makes working code.
For anyone trying to back of the napkin at $1000 as 4-figures per year, averaged as a day salary, the baseline salary where this makes sense is about ~$260,000/yr? Is that about right lordnacho?
And that's not saying AI tools are the real deal, either. It can be a lot less than a fully self driving dev and still be worth a significant fraction of an entry level dev.
> it's a very complicated and very powerful new tool that you need to practice using over time in order to get good results from.
Of course this is and would be expected to be true. Yet adoption of this mindset has been orders of magnitude slower than the increase in AI features and capabilities.One could even imagine going a step further and having a confidence level associated with different parts of the code, that would help the LLM concentrate changes on the areas that you're less sure about.
You can also literally do exactly what you said with "going a step further".
Open Claude Code, run `/init`. Download Superwhisper, open a new file at project root called BRAIN_DUMP.md, put your cursor in the file, activate Superwhisper, talk in stream of consciousness-style about all the parts of the code and your own confidence level, with any details you want to include. Go to your LLM chat, tell it to "Read file @BRAIN_DUMP.md" and organize all the contents into your own new file CODE_CONFIDENCE.md. Tell it to list the parts of the code base and give it's best assessment of the developer's confidence in that part of the code, given the details and tone in the brain dump for each part. Delete the brain dump file if you want. Now you literally have what you asked for, an "index" of sorts for your LLM that tells it the parts of the codebase and developer confidence/stability/etc. Now you can just refer to that file in your project prompting.
Please, everyone, for the love of god, just start prompting. Instead of posting on hacker news or reddit about your skepticism, literally talk to the LLM about it and ask it questions, it can help you work through almost any of this stuff people rant about.
Despite explicit instructions in all sorts of rules and .md’s, the models still make changes where they should not. When caught they innocently say ”you’re right I shouldn’t have done that as it directly goes against your rule of <x>”.
Just to be clear, are you suggesting that currently, with your existing setup, the AI’s always follow your instructions in your rules and prompts? If so, I want your rules please. If not, I don’t understand why you would diss a solution which aims to hardcode away some of the llm prompt interpretation problems that exist
In essence, you have to do the "engineering" part of the app and they can write the code pretty fast for you. They can help you in the engineering part, but you still need to be able to weigh in whatever crap they recommend and adjust accordingly.
Worth it to me as I can fix all the above after the fact.
Just annoying haha