- Ray Lu leading the Junyi Academy Foundation team
- Organization-wide (full NPO team)
An education-focused NPO has finite resources but ten times the work. If everyone uses their own AI, workflows fragment; if everyone uses just one, the tool's weaknesses become the team's. How do you turn "multi-AI" into "one organic AI team" rather than "a pile of disjointed AI tools"?
**Role definition**: Notion AI = the org's memory and project brain; Gemini = intel and fast research; Claude = deep reasoning, product building, demos. **Standardized workflow**: meetings open in Notion (auto-recorded) → action items into Notion projects → external research switches to Gemini → product building switches to Claude → outputs flow back into Notion to settle. **Team training**: every member fluent in all three AIs, with one specialty. **Continuous tuning**: weekly retros surface stuck workflows for targeted fixes.
The three-AI workflow went from personal know-how to organizational infrastructure: with resources far smaller than commercial counterparts, the team sustains steady output across intelligence, meetings, and product. New hires learn it in week one. Departing members take their experience, not the workflow (the workflow belongs to the org).
"Knowing how to use AI" is Basic. "Orchestrating multiple AIs" is Proficient. **"Designing the human/AI division so the whole org collaborates effectively" is Advanced** — it demands clarity on what humans do, what AI does, where the boundary is, and how quality is gated. OUTCOME = compounding organizational throughput; IMPACT = an NPO moving at commercial-company speed. This is Manage · Advanced: integrating the human-AI hybrid team.
