The Problem with Monolithic Tools
Most AI platforms are built as single, monolithic applications. You get one interface, one context window, one set of tools — regardless of what you're trying to do.
This creates two problems.
First, context collapse. When everything happens in one place, conversations bleed together. Your learning session gets mixed with your work project. Your brainstorm interrupts your focused study. The AI doesn't know which context you're in.
Second, cognitive overload. Universal tools require you to specify what you want on every turn. You become the prompt engineer, the context manager, the mode selector. The tool is flexible, but the burden is yours.