Task Management & Time Management

My current design approach is to separate task management from time tracking, and reduce operational overhead through automation.

I. Task Management System At its core is a structure similar to a Notion database, where each record represents an indivisible "atomic task" containing metadata such as task name and time attributes. The key design is that each record can link to an independent page for storing detailed context, reference materials, or thought processes related to the task. When users switch between tasks, they can quickly restore context by checking the corresponding page, avoiding cognitive load.

II. Time Tracking System A "Session Table" is used to record the actual time a user spends on specific tasks. Its logic works as follows:

1. When a user clicks "Start Task" on a task page, an automation script creates a new record in the session table, marking the task ID and start time.
2. When the user switches to another task and clicks "Start," the script automatically ends the previous session and records the end time.
3. By calculating the difference between the start and end times of each session, the actual time spent on each task can be tallied.

III. Current Issues and Optimization Directions

1. High overhead for short tasks: For tasks that take very little time (e.g., passing on a message), the manual effort of creating a record, opening the page, and filling in context may far exceed the task itself.
   • Solution: Introduce AI-powered automatic capture. In office suites (e.g., Feishu, WeChat Work), AI can recognize task intent in chats and emails, automatically generate task records, and associate context. Meanwhile, by monitoring users' computer activity, AI can further match tasks with time sessions automatically, enabling frictionless recording.
2. Recording offline scenarios: Face-to-face conversations and other offline interactions are difficult to track automatically.
   • Proposed approach: Use a portable recording device (e.g., Anker Pod) to start recording with one tap during a conversation, and automatically generate structured text via Feishu meeting notes. However, privacy concerns and the feeling of being "monitored" need to be addressed.
   • Trade-off: At the current stage, if the user base consists of independent developers or people with control over their own time, offline interruptions are relatively rare, so the need for full-scenario automatic sensing may not be urgent.

IV. Product Positioning and Design Principles

1. Target users: Focus on people who have "a large amount of autonomous time to manage" (e.g., freelancers, independent developers), rather than aiming for an "all-in-one" tool covering every scenario. This significantly reduces system complexity.
2. Interaction principle: The tool itself should be extremely simple, so users don't waste time operating the tool. The core is "peace of mind"—let users focus on execution, while the system actively prompts the next task, tasks approaching deadlines, or to-do lists.
3. Current priority: Achieve automatic association between tasks and time (e.g., when collaborating with OpenAI, automatically log research tasks into the system), rather than building complex traditional table interfaces (like Trello, Monday.com).

V. Core Value Proposition Help users establish a "sense of control" over time: through frictionless recording and intelligent prompts, reduce manual management burden, so users can concentrate on the tasks themselves, and clearly understand where their time goes and task priorities when needed.