Pragmatic AI

Fillmer Innovation Group's guiding principles for AI Transformation.

Buy In, Not Plug In

Plugging in an AI platform is not transformation. Factories that swapped the steam engine for an electric motor and changed nothing else wasted thirty years of productivity. The gains came when they redesigned the floor around the new technology. It is no different with AI.

Human Centric

Solutions imposed from outside do not stick. Let the people doing the work drive the redesign; they know where the pain lives. Redesigned processes are owned by the people who run them and coordinated across the business. Design that serves the business, adoption that sticks.

Create Upside

Most AI transformations focus on saving time and money, but fall short of scaling revenue. Better context produces better decisions, better decisions produce growth, and growth compounds. A well-designed system delivers top-line growth and efficiency gains together.

Boring Tiny Tools

Practical, highly customized, and narrowly scoped tools that work with your existing software solutions. A catch-all for everything from a clever prompt to a custom integration to a full agentic loop. Thanks to Generative AI coding tools, the cost of building custom software is low enough to bring real solutions to more businesses.

Meet People Where They Are

Use AI to deliver results inside tools people already open every day. The email thread, the spreadsheet, the chat tool. Minimize the change a new workflow demands and build on existing usage habits. Systems that demand the least behavioral change get used.

Chesterton's Fence

Understand why something exists before changing it. The process exists for a reason, even if nobody remembers what it is. Map every workflow end to end, capture the tribal knowledge buried inside it, and convert that knowledge into rules and decision logic before touching anything.

Crawl Before You Walk

Automation is the destination, not the starting line. Start with the workflow as it already runs. AI puts automation within reach that wasn't there before, and the groundwork laid feeds what is built later. Iterate, streamlining and automating once the manual version proves out. Then stop when removing the next bit of pain costs more than the pain itself.

Minimize AI Surface Area

Consistency in handling structured data is non-negotiable. An AI that follows a set process you can check at each step is better than one that makes it up as it goes. Keep AI touch-points small, well-defined, and deterministic. The fewer places AI introduces variance, the more reliable the system.