We're drowning in tools. As AI makes it trivial to build software for extremely narrow problems, we risk creating a tool zoo that demands more attention than it saves.
Professionals are already overwhelmed by vendor choices and productivity tools competing for mindshare. We simply don't have the bandwidth or time to train on dozens of bespoke apps that each solve a tiny slice of work.
Artificially splintering AI into narrow, single-purpose apps is inefficient and unnecessary. When it's easy to build an app for every problem — and you have 50 similar problems — creating, maintaining, and training teams on 50 apps isn't scalable.
Most "tools" should really be prompts, specs, and workflows that spin up solutions through a single, effective AI harness.
Maintaining one model-agnostic harness — to avoid lock-in — that can generate those 50 solutions on-demand is the better path. The expertise lives in your prompts, skills, and workflows. The harness executes them. You don't need 50 apps; you need 50 well-crafted prompts and a platform that can run them.
This is the direction VerbaGPT is built toward. Not a narrow analytics tool, but a harness that grows with your use cases — through Prompt Libraries, Agent Skills, Data Notes, and reusable projects. The more you invest in the harness, the more capable it becomes across problems.
The tool zoo has a maintenance cost and a cognitive cost. The harness has a different kind of investment, and a much higher ceiling.
Originally posted on LinkedIn · January 14, 2026