Why good prompting is the #1 skill most AI builders still ignore
I’ve been experimenting a lot with AI tools like V0, Lovable, and Bolt.new to build small products and prototypes.
One pattern keeps showing up: most ideas don’t fail because the idea is bad. They fail because the prompt is vague, confusing, or incomplete.
AI isn’t a mind reader; it does exactly what you ask. If your prompt is fuzzy, your output will be too.
For example, I recently built PublicWall off a single well-structured prompt. Before that, I wasted hours on iterations that were mostly me not clarifying what I actually wanted the AI to do.
To help with this, I started using PromptCraft to clean up and structure my ideas. It’s been a big time-saver. But more importantly, it’s taught me how crucial prompt design is to building anything worthwhile with AI.
I’m curious how others here approach this:
How do you craft prompts for AI tools when building products?
Do you have any systems or best practices you follow to get better outputs?
Are there tools, frameworks, or examples you’d recommend for improving prompt clarity?
Would love to hear your experiences, tips, or any resources that have helped you write better prompts.
Replies
This should be the first thing people learn before using any AI.
Dereference
@michael_t_brown How come?
Couldn't agree more. The tighter the prompt, the better the output. Period.
Personally, I use it with dev a lot and I’ve found giving AI tools structured READMEs, constraints, limitations, and clear design intentions makes a huge difference. Treating it like a junior dev with specs gets me so much closer to what I want, thinking that way's worked wonders for me.
Dereference
That’s 🔥 I’ve been building dereference.dev to bring more structure to exactly this kind of prompt-first dev workflow.
Do you find yourself repeating prompt patterns or evolving them case by case?
Would be curious how your system compares . launching soon.