TaskPlexus

I built TaskPlexus after struggling with daily planning myself. Whenever I had a large number of todos—current and future—I felt scattered. Important tasks would get buried, and it was hard to visualize where I was or what to start with. I realized the real problem wasn’t creating more tasks, but gaining clarity. Progress depends almost entirely on executing today’s work well, not overplanning the future. That insight led to focusing the system strictly on daily planning. TaskPlexus uses a backend-controlled approach where the system decides which tasks are eligible, how priorities are ordered, and how much time can realistically be scheduled. The AI only works within these constraints, which avoids hallucinated tasks and unrealistic plans. I built the product incrementally—starting from data modeling, backend logic, and a simple frontend demo—then adding offline-first syncing, usage limits, and reliability safeguards. AI tools helped speed up iteration, but all system design decisions were handled manually. The goal was not feature count or UI polish, but a planning system that is predictable, realistic, and mentally manageable.