Building Useful AI

Artificial intelligence is quickly becoming part of the software people use every day. But simply adding an AI model to a product does not automatically make that product useful.

For us, the interesting question is not whether a product uses AI. The more important question is whether AI makes the experience meaningfully better for the person using it.

That distinction influences how we think about every AI-powered feature we build at Proxil.

A common mistake when building AI products is starting with the technology and looking for somewhere to use it. We prefer to start with a real problem.

Once the problem is clear, AI becomes one possible tool for solving it. Sometimes it may be the right tool. Sometimes a simpler piece of software may be better.

This approach keeps the product focused and prevents AI from becoming a feature that exists simply because it sounds impressive.

Good AI experiences depend heavily on context. The same question can require a very different answer depending on who is asking, what they are trying to accomplish, and what information is already available.

That is why useful AI products need more than a model and a text box. They need the right inputs, sensible product flows, useful feedback, and an experience that helps people understand what to do next.

The surrounding product experience matters just as much as the intelligence behind it.

AI can make software extremely powerful, but power does not have to mean complexity.

We want the products we build to feel straightforward. Users should be able to understand what a feature does, use it without unnecessary friction, and get an outcome that actually helps them.

The best AI experience is often the one where the technology fades into the background and the user simply feels that the product worked.

At Proxil, we are interested in AI that improves real workflows, reduces unnecessary effort, and helps people make progress.

That means experimenting with new technology while staying grounded in product fundamentals: clarity, reliability, usability, and purpose.

As AI continues to evolve, that philosophy will remain important to us. We want to build AI products that people can actually use, not just products that can demonstrate what a model is capable of.