I usually do most of the engineering and it works great for writing the code. I’ll say:

> There should be a TaskManager that stores Task objects in a sorted set, with the deadline as the sort key. There should be methods to add a task and pop the current top task. The TaskManager owns the memory when the Task is in the sorted set, and the caller to pop should own it after it is popped. To enforce this, the caller to pop must pass in an allocator and will receive a copy of the Task. The Task will be freed from the sorted set after the pop.

> The payload of the Task should be an object carrying a pointer to a context and a pointer to a function that takes this context as an argument.

> Update the tests and make sure they pass before completing. The test scenarios should relate to the use-case domain of this project, which is home automation (see the readme and nearby tests).

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logicprog an hour ago | parent | next [-]

Yeah, I feel like I get really good results from AI, and this is very much how I prompt as well. It just takes care of writing the code, making sure to update everything that is touched by that code guided by linters and type-checkers, but it's always executing my architecture and algorithm, and I spend time carefully trying to understand the problem before I even begin.

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gedy 7 hours ago | parent | prev | next [-]

What you’re describing makes sense, but that type of prompting is not what people are hyping

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Leherenn 6 hours ago | parent | next [-]

I haven't tried it, but someone at work suggested using voice input for this because it's so much easier to add details and constraints. I can certainly believe it, but I hate voice interfaces, especially if I'm in an open space setting.

You don't even have to be as organised as in the example, LLMs are pretty good at making something out of ramblings.

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ljm 6 hours ago | parent | prev [-]

The more accurate prompt would be “You are a mind reader. Create me a plan to create a task manager, define the requirements, deploy it, and tell me when it’s done.”

And then you just rm -rf and repeat until something half works.

	▲	varispeed 3 hours ago \| parent [-]
		"Here are login details to my hosting and billing provider. Create me a SaaS app where customers could rent virtual pets. Ensure it's AI and blockchain and looks inviting and employ addictive UX. I've attached company details for T&C and stuff. Ensure I start earning serious money by next week. I'll bump my subscription then if you deliver, and if not I will delete my account. Go!"

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varispeed 3 hours ago | parent | prev | next [-]

This is a good start. I write prompts as if I was instructing junior developer to do stuff I need. I make it as detailed and clear as I can.

I actually don't like _writing_ code, but enjoy reading it. So sessions with LLM are very entertaining, especially when I want to push boundaries (I am not liking this, the code seems a little bit bloated. I am sure you could simplify X and Y. Also think of any alternative way that you reckon will be more performant that maybe I don't know about). Etc.

This doesn't save me time, but makes work so much more enjoyable.

	▲	logicprog 42 minutes ago \| parent [-]
		> I actually don't like _writing_ code, but enjoy reading it. I think this is one of the divides between people who like AI and people who don't. I don't mind writing code per se, but I really don't like text editing — and I've used Vim (Evil mode) and then Emacs (vanilla keybindings) for years, so it's not like I'm using bad tools; it's just too fiddly. I don't like moving text around; munging control structures from one shape to another; I don't like the busy work of copying and pasting code that isn't worth DRYing, or isn't capable of being DRY'd effectively; I hate going around and fixing all the little compiler and linter errors produced by a refactor manually; and I really hate the process of filling out the skeleton of an type/class/whatever architecture in a new file before getting to the meat. However, reading code is pretty easy for me, and I'm very good at quickly putting algorithms and architectures I have in my head into words — and, to be honest, I often find this clarifies the high level idea more than writing the code for it, because I don't get lost in the forest — and I also really enjoy taking something that isn't quite good enough, that's maybe 80% of the way there, and doing the careful polishing and refactoring necessary to get it to 100%.

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apercu 6 hours ago | parent | prev [-]

This is similar to how I prompt, except I start with a text file and design the solution and paste it in to an LLM after I have read it a few times. Otherwise, if I type directly in to the LLM and make a mistake it tends to come back and haunt me later.