Most people blame AI when they don’t get the answers they want. Truth is, the problem usually isn’t the AI—it’s the prompt. Think of it this way: if you ask a vague question, you’ll get a vague answer. But when you give the AI a detailed, crystal-clear briefing, it becomes less of a search bar and more of a personal strategist. Let’s break this down with an example.

Most people trying to integrate AI into their workflow are making it way harder than it needs to be. Either they try to bite off more than they can chew, or they assume they need to master some black magic-level prompting to get results. Let’s bust that up.

If your GPT-5 results have felt a little… underwhelming, you’re not imagining things. Pietro Schirano, CEO of Magic Path, recently dropped a comprehensive GPT-5 prompting guide that explains why — and how to fix it. The short version? GPT-5 is way more sensitive to instruction style than earlier models, and most of us are still prompting like it’s GPT-4.

If you’ve been exploring AI tools like Claude, you’ve probably hit that wall where the outputs feel hit-or-miss. One day it’s genius, the next it’s a head-scratcher. That inconsistency usually points back to one thing: your prompts.

Ready to build a prompt engine inside your AI? Here’s how the pros do it:

Here’s the truth: the issue isn’t AI. It’s how you’re using it. With a few simple techniques, you can turn inconsistent results into precision-level outputs that align with your role, industry, and expectations. Let’s break down the three most effective ways to get AI to work for you—not against you.