AI Observer / Runtime-Aware Dev Agent

Follow-up: user feedback analysis and product simplification principle I want to add one more important lesson from real usage: the biggest risk is not missing another advanced feature, but making the tool too complex. The core user pain is this: separate pieces used to work, and the user only wanted a convenient launcher and a nicer interface. But when too much architecture, too many panels, too many controls, and too much logging are added, the result can become slower, harder to use, and less stable. For this kind of runtime-aware assistant, the product principle should be: do not make it more complex; make it more convenient. Every new feature should answer one question: does this actually make work faster, simpler, or more stable? If not, it should not be added to the main UI. The popup should stay minimal. It should be a launcher, not a developer dashboard. Workers should do the background work. AI should help with text and decisions. Browser/runtime observation should stay focused and explain what is actually being verified. The old working mechanics should be preserved first: inject logic, reply logic, like logic, the existing reply database, speed, and separate workflows. New architecture should wrap the working mechanics carefully instead of replacing them with a bigger system. A good minimal UI would show only the essentials: likes/hearts, saved replies, AI on/off, stop, reply count, speed, and one-line status. Debug panels, giant logs, worker controls, readiness tables, and extra settings should be hidden unless explicitly needed. The main message is simple: a runtime-aware AI tool should feel small, fast, stable, and useful. It should not become a giant AI control center.