Building AI Systems That Feel Human

The AI boom has brought endless hype, but the real challenge isn't building AI—it's building AI that people actually want to use. Here's what I've learned designing WADL and other AI products.

The Problem with Most AI Products

Too many AI tools feel like tech demos. They're impressive for 30 seconds, then you realize they don't fit into your actual workflow. The issue isn't the AI—it's that most builders focus on capability over usability.

When I started building WADL, I made the same mistake. I wanted to showcase everything AI could do. But then I talked to actual business owners, and they didn't care about what was possible. They cared about what was practical.

Clarity Over Capability

Here's what I learned: the best AI products don't feel like AI products. They feel like solutions. When someone uses WADL's Deal Triage Assistant, they're not thinking "wow, this is using GPT-4 to score pitches." They're thinking "this just saved me two hours."

That's the difference. Clarity beats capability every time.

Three Principles for Human-Centered AI

1. Start with the Problem, Not the Technology

Don't ask "what can AI do here?" Ask "what's the actual pain point?" Then see if AI is the right tool. Sometimes it's not. Sometimes a simple filter or a better UI is all you need.

2. Make It Feel Intentional

AI should feel deliberate, not magical. When WADL's monitoring agent escalates an issue, it tells you why. When the research agent provides an answer, it shows its sources. No black boxes.

3. Design for Trust

People won't use tools they don't trust. Build transparency into every interaction. Show the reasoning. Let users override decisions. Make it clear that the AI is a tool, not a replacement for human judgment.

Building WADL: A Case Study

WADL started as a generic "AI consultancy." Vague. Unhelpful. So we repositioned: we're a Fractional Chief AI Officer. Companies know what a Chief AI Officer does—strategy, implementation, results. Adding "fractional" makes it accessible to SMBs who can't hire full-time.

Same with our product stack. We didn't build "an AI platform." We built three specific tools: a monitoring agent, an escalation agent, and a dashboard. Each solves one problem really well.

What's Next

I'm working on two more products: a recruiting AI that automates candidate sourcing, and improvements to the Deal Triage system. Both follow the same philosophy: clarity, intentionality, and trust.

If you're building AI products, ask yourself: does this feel human? Would I actually use this? If not, keep iterating.

Conclusion

AI is just a tool. The real work is understanding people, designing thoughtful systems, and building products that actually make sense. Focus on that, and the AI will take care of itself.