Even the best AI cannot predict what a real human does inside your system.
This week I noticed the same pattern show up with two clients and a business partner. It is a pattern that looks like professionalism on the surface, but often feels like quiet fear underneath.
We try to design the perfect platform before anyone uses it.
One client serves a user base that is not tech-savvy. He wants to protect them from confusion and deliver an enterprise-level experience. So the instinct is to keep adding safeguards and features in advance.
The intention is good.
But the system has not been used yet, and that is where the strategy breaks.
Another client said a sentence that dissolves the fantasy of certainty.
Until I actually start using it, everything is theoretical.
A partner’s story made the lesson even clearer. Early in his product journey, he prioritized built-in forms because it felt like a core feature. Two years later, customers barely asked for it because strong alternatives already existed and integrated well.
That is the uncomfortable truth.
You can plan for weeks. You can use AI to pressure test scenarios. You can create a beautiful roadmap.
And the moment real humans touch the system, reality gets a vote.
AI may help you think faster and document better. It may help you map workflows and surface edge cases.
It does not replace lived behavior.
A practical approach that often creates momentum without sacrificing quality looks like this:
- Define the minimum safe experience Focus on the first win a user needs, and what truly must not break.
- Ship v1 to a small group Aim for 5 to 20 users so you can watch closely and learn quickly.
- Improve the 20 percent that changes adoption Track where people hesitate, where they get confused, and what they request repeatedly.
AI Superstar Hack (30 to 60 minutes)
Use ChatGPT or Gemini to turn raw feedback into a weekly roadmap.
- Ask the model to generate a short user test plan with 8 to 12 tasks
- Run three tests, capture notes in plain text
- Paste notes back into the model and ask for categorization: must-fix, training gap, nice-to-have, ignore for now
- Pick one improvement to ship this week
AI is a multiplier. Users are the compass.
