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Ask HN: How can I get better at using AI for programming?

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31–40 of 491 posts

Re: Ask HN: How can I get better at using AI for programming?

#31
Voice prompts, restate what you want, how you want it from multiple vantage points. Each one is a light cone in a high dimensional space, your answer lies in their intersection.

Use mind altering drugs. Give yourself arbitrary artificial constraints.

Try using it in as many different ridiculous ways you can. I am getting the feeling you are only trying one method.

> I've had a fairly steady process for doing this: look at each route defined in Django, build out my `+page.server.ts`, and then split each major section of the page into a Svelte component with a matching Storybook story. It takes a lot of time to do this, since I have to ensure I'm not just copying the template but rather recreating it in a more idiomatic style.

Relinquish control.

Also, if you have very particular ways of doing things, give it samples of before and after (your fixed output) and why. You can use multishot prompting to train it to get the output you want. Have it machine check the generated output.

> Simple prompting just isn't able to get AI's code quality within 90%

Would simple instructions to a person work? Esp a person trained on everything in the universe? LLMs are clay, you have to mold them into something useful before you can use them.

Re: Ask HN: How can I get better at using AI for programming?

#32

Here’s how I would do this task with cursor, especially if there are more routes. I would open a chat and refactor the template together with cursor: I would tell it what I want and if I don’t like something, I would help it to understand what I like and why. Do this for one route and when you are ready, ask cursor to write a rules file based on the current chat that includes the examples that you wanted to change an…

Solid approach. Don’t be shy about writing long prompts. We call that context engineering. The more you populate that context window with applicable knowledge and what exactly you want, the better the results. Also, having the model code and you talk to the model is helpful because it has the side effect of context engineering. In other words you’re building up relevant context with that conversation history. And be acutely aware of how much context window you’ve used and how much is remaining and when a compaction will happen. Clear context as early as you can per run. Even if it’s 90% remaining.

Re: Ask HN: How can I get better at using AI for programming?

#33
post #22

How did you learn how to use AI for coding? I'm open to the idea that a lot of "software carpentry" tasks (moving/renaming files, basic data analysis, etc) can be done with AI to free up time for higher level analysis, but I have no idea where to begin -- my focus many years ago was privacy, so I lean towards doing everything locally or hosted on a server I control so I lack a lot of knowledge of "the cloud" my HN be…

I love the name "software carpentry" haha.

IMO, I found those specific example tasks to be better handled by my IDE's refactoring features, though support for that is going to vary by project/language/IDE. I'm still more of a ludite when it comes to LLM based development tools, but the best case I've seen thus far is small first bites out of a big task. Working on an older no-tests code base recently, it's been things like setting up 4-5 tests that I'll expand on into a full test suite. You can't take more than a few "big" bites out of a task before you have 0 context as to what direction the vector soup sloshed in.

So, in terms of carpentry, I don't want an LLM framer who's work I need to build off of, but an LLM millworker handing me the lumber is pretty useful.

Re: Ask HN: How can I get better at using AI for programming?

#34
post #8

I see LLMs as searchers with the ability to change the data a little and stay in a valid space. If you think of them like searchers, it becomes automatic to make the search easy (small context, small precise questions), and you won't keep trying again and again if the code isn't working(no data in the training). Also, you will realize that if a language is not well represented in the training data, they may not work…

This is slightly flawed. LLMs are search but the search space is sparse, the size of the question risks underspecification. The question controls the size of the encapsulated volume in that high dimensional space. The only advantage for small prompts is computational cost. In every other way they are a downside.

Re: Ask HN: How can I get better at using AI for programming?

#36
post #22

How did you learn how to use AI for coding? I'm open to the idea that a lot of "software carpentry" tasks (moving/renaming files, basic data analysis, etc) can be done with AI to free up time for higher level analysis, but I have no idea where to begin -- my focus many years ago was privacy, so I lean towards doing everything locally or hosted on a server I control so I lack a lot of knowledge of "the cloud" my HN be…

Practice on an open source repo to allay your privacy fears.

Re: Ask HN: How can I get better at using AI for programming?

#37
Hey, Boris from the Claude Code team here. A few tips:

1. If there is anything Claude tends to repeatedly get wrong, not understand, or spend lots of tokens on, put it in your CLAUDE.md. Claude automatically reads this file and it’s a great way to avoid repeating yourself. I add to my team’s CLAUDE.md multiple times a week.

2. Use Plan mode (press shift-tab 2x). Go back and forth with Claude until you like the plan before you let Claude execute. This easily 2-3x’s results for harder tasks.

3. Give the model a way to check its work. For svelte, consider using the Puppeteer MCP server and tell Claude to check its work in the browser. This is another 2-3x.

4. Use Opus 4.5. It’s a step change from Sonnet 4.5 and earlier models.

Hope that helps!

Re: Ask HN: How can I get better at using AI for programming?

#38
> prompting just isn't able to get AI's code quality within 90% of what I'd write by hand

Tale as old as time. The expert gets promoted to manager, and the replacement worker can’t deliver even 90% of what the manager used to. Often more like 30% at first, because even if they’re good, they lack years of context.

AI doesn’t change that. You still have to figure out how to get 5 workers who can do 30-70% of what you can do, to get more than 100% of your output.

There are two paths:

1. Externalized speed: be a great manager, accept a surface level understanding, delegate aggressively, optimize for output

2. Internalized speed: be a great individual contributor, build a deep, precise mental model, build correct guardrails and convention (because you understand the problem) and protect those boundaries ruthlessly, optimize for future change, move fast because there are fewer surprises

Only 1 is well suited for agent-like AI building. If 2 is you, you’re probably better off chatting to understand and build it yourself (mostly).

At least early on. Later, if you nail 2 and have a strong convention for AI to follow, I suspect you may be able to go faster. But it’s like building the railroad tracks before other people can use them to transport more efficiently.

Django itself is a great example of building a good convention. It’s just Python but it’s a set of rules everyone can follow. Even then, path 2 looks more like you building out the skeleton and scaffolding. You define how you structure Django apps in the project, how you handle cross-app concerns, like are you going to allow cross-app foreign keys in your models? Are you going to use newer features like generated fields (that tend to cause more obscure error messages in my experience)?

Here’s how I think of it. If I’m building a Django project, the settings.py file is going to be a clean masterpiece. There are specific reasons I’m going to put things in the same app, or separate apps. As soon as someone submits a PR that craps all over the convention I’ve laid out, I’m rejecting aggressively. If we’ve built the railroad tracks, and the next person decides the next set of tracks can use balsa wood for the railroad ties, you can’t accept that.

But generally people let their agent make whatever change it makes and then wonder why trains are flying off the tracks.

Re: Ask HN: How can I get better at using AI for programming?

#40
post #10

Using voice transcription is nice for fully expressing what you want, so the model doesn't need to make guesses. I'm often voicing 500-word prompts. If you talk in a winding way that looks awkward when in text, that's fine. The model will almost certainly be able to tell what you mean. Using voice-to-text is my biggest suggestion for people who want to use AI for programming (I'm not a particularly slow typer. I can…

surprised ai companies are not making this workflow possible instead of leaving it upto users to figure out how to get voice text into prompt.
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