Ever built something that worked perfectly... and nobody used it?

Most AI agent projects don't fail because the agent is bad. They fail because nobody trusts it enough to use it. I've seen teams spend weeks building impressive demos. The agent works. The outputs are good. Everyone gets excited. Then it never makes it to production. Why? Because the real questions start showing up: * What data can it access? * Who is responsible if it makes a mistake? * How do we know what it's doing? * Can we audit its decisions? * Can we shut it down when something goes wrong? Suddenly the model isn't the problem. Trust is. Building the agent is often the easy part. Making it trustworthy is the hard part. That's why observability matters so much. If you can't see what an agent is doing, you won't trust it. And if you don't trust it, you'll never deploy it. The biggest bottleneck in enterprise AI isn't intelligence. It's trust.