Last week I pasted a screenshot of a broken UI into an AI assistant. Two buttons were ridiculously huge.
The AI ignored them completely and started talking about something else.
I was shocked. But then I realized: I was asking it to read my mind.
The Real Problem Isn't AI—It's Precision
When your UI gets even slightly complex, you cannot reliably describe what's wrong in a way that makes the model target exactly what you mean. It changes code in the wrong component, edits multiple files, renames things, and suddenly you're debugging the AI's output instead of the actual bug.
This wastes time, wrecks maintainability, introduces bugs, and gets expensive fast.
Three Strategies That Actually Work
After months of frustration, I developed three precision strategies that force AI assistants to hit the target every time:
🎯 Strategy 1: The Inspector Trick
Stop describing UI problems in words. Extract exact element data (selectors, bounding boxes, CSS classes) and feed that to the AI. It's like giving a surgeon GPS coordinates instead of saying "it's somewhere in the chest area."
📖 Strategy 2: The Terminology Document
AI drifts between "Task," "Todo," and "Item" without consistency. Create a single source of truth for what everything is called. One term per concept, enforced everywhere.
🎨 Strategy 3: HTML Variations First
Never redesign in your codebase. Create 3-4 variations in standalone HTML files first, test them visually, then implement the winner. No more refactoring disasters.
The Bottom Line
Stop treating AI like a magic wand. Treat it like a talented junior developer who needs exact specifications. The quality of code you get out is directly proportional to the precision of context you put in.
Want the full implementation details, code examples, and ready-to-use prompts?
👉 Read the complete article here: Your AI Isn't Stupid—Your Instructions Are Too Vague
Includes copy-paste-ready prompts for Cursor, Claude Code, and other vibe coding tools.
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