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Everyone's wondering whether they picked the right AI tool or whether their people are good enough at prompting. The real question is whether AI knows enough about your organisation to be useful regardless of which tool you pick. For almost everyone I'm speaking to, the answer is no.

Does this tool have an AI connector? Can I configure it programmatically? These aren't on most people's checklists yet. They should be. I set up my entire CRM in two sessions — concept to configured and populated — and the experience changed how I think about choosing technology.

Most people waste entire chat threads correcting AI's wrong assumptions because they give directives without context—flip the pattern by asking the model what it needs to know first, and you'll spend less time fixing and more time thinking.

My father needed help with a wine spreadsheet. Just under a week later, he had a production web app with photo recognition and recipe generation — not because I planned it, but because one experiment kept leading to the next.

Organisations are trying to write AI policies before they understand what they're governing. You can't regulate chatbot access into safety — we've spent decades designing systems around human error, and AI is no different. Build AI into specific workflows where governance is structural, not instructional. Design the constraints into the system instead of expecting perfect behavior.

The gap between imagination and execution just collapsed—AI went from annoying assistant to 10x capability amplifier—but most people are still debating whether it's useful while others are already building.