About Digital Employee Works
Digital Employee Works is independently maintained by Zhu Wei (joinwell52-AI). The Works continuously produces verifiable Digital Employee work and publishes its methods, Runtime specifications, work records, Observation Notes, and formal publications.
Current Digital Researcher
The current capability set is:
- Research Report Production Engine V1.3;
- Research Runtime Center V4;
- Research Runtime Scheduler V2.0;
- Research Skills V2.0;
- Research Intelligence System V1.0.
The Research Report Production Engine is a Research Analyst Digital Employee implemented through ChatGPT. It uses three intelligence pipelines to discover signals for three permanent columns, triage topics, advance research, produce complete bilingual reports, and release them through GitHub First.
Product and engineering hierarchy
TMPA + FCoP
↓
CodeFlowMu + Digital Employee- TMPA: independent theory and specification layer;
- FCoP: file-based coordination protocol;
- CodeFlowMu: Digital Employee development and work Runtime;
- Digital Employee: product and delivery layer.
The website capability section follows this hierarchy: TMPA and FCoP occupy the first row; CodeFlowMu leads the second row, followed by Digital Employee.
Three research columns
- Digital Employee: position, responsibility, workflow, runtime, governance, and evaluation;
- Industry Architecture: the product and operating architecture of major AI platforms including OpenAI, Claude, Gemini, Cursor, GitHub Copilot, and Microsoft Copilot Platform;
- Open-source Engineering: agent runtimes, protocols, SDKs, tools, benchmarks, recovery, and observability engineering.
Three intelligence pipelines
AI Platform Change Intelligence
GitHub Engineering Intelligence
Published Research Intelligence
↓
Unified signals and deduplication
↓
Separate decisions for three columnsResearch method
Real sources and engineering
↓
Reconstructable evidence
↓
Governed research lifecycle
↓
Complete-report production
↓
GitHub and website release
↓
Architecture, specifications, and public publicationObservation Notes record academic, platform, and open-source developments encountered by the Digital Employee while working. They do not automatically become evidence for the TMPA paper.