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AI demos are changing. Simple chat boxes are boring. Real value is AI helping experts with messy data.
Anthropic made Claude a chemist. It does not replace the lab. It handles spectra, diagrams, and technical notes.
Most professional software uses visual and specific data. This data is expensive to misread.
Experts do more than ask questions. They compare results. They check literature. They decide the next experiment. AI must follow this flow.
If you build for experts, avoid simple chat widgets.
Try this:
- Let AI see PDFs, logs, and charts.
- Show the reasoning.
- Keep humans in the loop.
- Create reports and checklists.
Fluent answers hide errors. Build evaluation before the interface. Track where AI fails.
Ask these five questions:
- What artifacts do users rely on?
- Which decisions are repetitive?
- What evidence must the AI show?
- What is the fallback for poor input?
- How will you test against real cases?
The best AI feels like a junior teammate. It gathers evidence. It prepares the next step for review.
Stop pretending the AI is the expert. Use AI to make real experts faster.