I thought AI would be the hardest part of building PulseBoard. I was wrong...

A few days after launching PulseBoard, I had several founders ask me nearly the same question:

"How does the AI actually know why my website failed?"

At first, I thought they were questioning the idea.

They weren't.

They were questioning whether they could trust the AI.

That completely changed how I think about building an AI product.

PulseBoard currently analyzes monitoring telemetry such as response times, HTTP status codes, latency patterns, uptime history, and incident behavior to generate confidence-aware explanations of what most likely happened.

But it doesn't have access to server logs, WordPress internals, or AWS metrics unless those integrations exist.

I realized something important:

Developers don't expect AI to magically know everything.

They expect it to be honest about what it knows, what it doesn't know, and why it reached a particular conclusion.

So I'm doubling down on three principles for Vigil AI:

• Never invent a root cause that isn't supported by evidence.

• Explain the reasoning behind every AI-generated analysis.

• Be transparent about confidence instead of pretending certainty.

Ironically, launching the product taught me that the challenge isn't building AI.

The challenge is building trust.

I'm curious—if you're building an AI product, what's the hardest trust-related problem you've run into?