Bespoke technology · since 2000

The human aspects of the system, not just the technology.

We aren’t building technology for the sake of technology. We consider the human aspects of the system — and acknowledge that there is a system. Sometimes the solution is a human solution, not a technical one.

Meet Dr.Wayne PhD with 30 years of entrepreneurial experience

The arc

It started with IT support. It has deepened every era since.

Each era compounded on the last. The thread connecting all of it: understanding the situation and the desired outcomes before reaching for the tools.

  1. The foundation

    IT support

    Hands on keyboards, fixing what was broken, learning the landscape of what businesses actually need from their technology day to day.

  2. The pivot

    Professional development

    NLP, Productive Tension, ethical sales, leadership, learning experience design, gamification as a motivational model. It expanded the vision of the context to get beyond just the technical solutions and focus on how people are actually “wired.”

  3. Already shaped

    Web development

    Primarily WordPress-based for small businesses. By this point the technical work was already shaped by the understanding that the system includes people, not just software.

  4. Where it lands today

    Custom SaaS & generative AI

    Where the Double Diamond approach proves incredibly useful: first we step back and make sure we understand the problem space before attempting a solution. The thread connecting all of it — understanding the situation and the desired outcomes before reaching for the tools.

We have had requests for custom software resolved by educating the client on features in the software they already had.
From twenty-eight years of practice

Intelligence augmented

AI is an amplifier of expertise — not a replacement for it.

The big discussions around generative AI claim that all skilled work will be done by AI soon. What we are seeing, working just behind the leading edge, is that the AI can only mimic the surface layer of task outputs. It doesn’t have the earned expertise behind the decision-making.

If you are already skilled in an arena, AI lets you move faster and go deeper. If you don’t know much in that area, it amplifies that tiny signal and mostly produces noise — which the lack of skill can’t catch and correct, so it compounds errors in odd ways like an overly confident intern.

This shifts the conversation to what aspects of the workflow make sense to use LLMs for, and where we are using human experience and expertise for now judging the work instead of doing it. Managing and evaluating the work is a different skill set than doing the work — and we aren’t having the conversations around what that means for the roles and individual capabilities needed for those shifting roles.