The problem and why it matters
When working with AI, ideas remain in conversations, tasks live in separate tools, and execution creates more files and decisions. Continuing a project requires explaining the background again, finding materials and reorganizing plans.
- Context continuity
- Goals, decisions and results need stable storage and relationships after a conversation ends.
- Work planning
- Not every quick input should become a task; actions, materials and ordinary records need to be distinguished.
- Operational burden
- Moving information repeatedly between a web interface and assistant increases the effort needed to organize and advance work.
Intent connects inputs, projects, tasks, materials and actions around these practical problems. The aim is to make it easier to find supporting context, make decisions and continue the next step.
Delivered capabilities and remaining validation
| Delivered scope | Current status | Work supported |
|---|---|---|
| Personal workspace | A running instance with validated desktop and mobile flows | Manage projects, tasks, materials and actions |
| MCP and assistant integration | The web interface and agent share business services, with actual integration acceptance records | Query and operate on the same working data |
| Daily organization reports | Organization reports and WeChat briefings are deployed | Turn original inputs into suggestions users can inspect and confirm |
| Attention and follow-up foundations | Attention, execution events and notification states are implemented and tested in isolation | Retain decision evidence and follow-up state |
Single WeChat deliveries and host execution reports have real acceptance records. Corrections and confirmations through real conversations, full progress after responses and long-term proactive contact still need validation. Existing tests do not establish the overall user outcome.
My scope of work
- Defined objects and relationships for records, goals, projects, tasks, materials and actions.
- Designed and developed a workspace centered on projects, recent materials and today's arrangements.
- Implemented business services and MCP interfaces, connecting my agent and WeChat entry point.
- Organized daily processing, material archiving, attention and follow-up capabilities, checking acceptance boundaries at each stage.
Users decide goals, priorities and formal tradeoffs. Product services retain official objects and state; AI helps organize and execute. Execution results still need acceptance against actual tasks.
Deliverables and key decisions
A workspace organized around projects
Projects connect tasks, materials and results. Quick capture, detail drawers, references and in-place task actions sit near the relevant work, helping users continue what they are already doing.
A path from original records to explicit confirmation
First retain the original text and source, then let AI generate an organization report. Users inspect the reasoning, correct classifications and explicitly confirm before formal objects and actions are created. Ordinary entries remain records, and archived materials need a future use.
- Retain original textInput and source
- Create a reportAI organization suggestions
- Check and correctUser judgement
- Explicit confirmationCreate formal objects
- Execute and retain resultsTasks, actions and results
The process above describes the main product flow. Real WeChat correction and confirmation exchanges still need ongoing acceptance in use.
Business data shared by the web interface and agent
The web interface and MCP query and update objects through the same product services. Skills describe organization and follow-up methods, OpenClaw connects WeChat, and assistant execution states return to the web interface and projects.
Attention and notifications also need to retain the basis for intervention, user responses and next-step conditions, so contact and follow-up decisions are recorded explicitly.
What this project demonstrates
The ability to start from practical daily burdens and design and build product objects, interactions, business services and agent integration, while validating functionality separately from actual experience.
This suits work where a personal assistant needs sustained project understanding and connections between materials and actions. Further evaluation focuses on suggestion usefulness, reduced operational burden and whether proactive follow-up creates a real feedback loop.
Project materials
Based on current product documentation and acceptance records for integration, daily reports and proactive attention, updated in October 2026.
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