Chapter 01
I started from engineering work
TiCDC at PingCAP, then AI infrastructure, vector databases, AI-native SaaS, commercialization, and platform work. Engineering taught me to ask how a product is actually used, not only how it is described.
About
About
Darren Su / 苏鹏
Based in Hangzhou. I started from engineering, grew through open-source and AI learning communities, and now work across AGI Villa, Datawhale, Product Lab, field events, and cross-border technology. The thread is simple: understand the field, gather the right people, and let real feedback shape the next step.
A useful bridge is not a contact list. It is knowing which serious people should meet, why now, and what feedback should change next.
Cross-border Tech ConnectorEngineer Turned Community BuilderAGI Villa Co-founderDatawhale City Lead
Chapter 02
Community changed how I understand growth
I joined Datawhale as an AI learner in 2019, then became a contributor, teaching assistant, organizer, and city lead. That work made community feel less like traffic and more like trust, feedback, and opportunity becoming visible.
Chapter 03
AGI Villa is my long-term experiment with AI founders
I co-founded AGI Villa to explore how AI and community create new products, teams, and founder support systems. It keeps me close to global AI builders, early products, and the moments when ideas need real users.
Chapter 04
Product Lab keeps my advice close to reality
I keep building because strategy gets weak when it is separated from users, distribution, and awkward early feedback.
Chapter 05
Long-term practice keeps the work grounded
Meditation, Zen study, and public-interest work help me stay simple, direct, and clear when AI, startups, and cross-border work move fast.
Why This Work
Why I keep building at this intersection.
AI moves fast, but useful innovation still depends on people who trust each other enough to test something real.
AGI Villa began from a belief in AI and community: creative people should be seen earlier, and early ideas should meet real feedback sooner. That same belief now shapes the cross-border work on this site. The goal is not to make a market feel abstractly exciting, but to create the first useful room, visit, demo, or conversation where a better decision can happen.
01
AI creates new products faster than old go-to-market playbooks can explain.
02
Community turns scattered interest into people, trust, and follow-through.
03
Focused feedback keeps ambition tied to users, partners, and real constraints.
Inner Ground
Slowing down is not leaving the field.
I have been drawn to the quiet process of incense burning. It is less a symbol to explain and more a reminder of rhythm: the faster the work moves, the more important it is to keep a stable point of attention.
See the problem clearly, treat people seriously, then move in small steps.
What This Supports
From background to practical cross-border work.
01
Translate an AI, robotics, hardware, open-source, or product question into the first useful China test.
02
Find the builders, communities, labs, suppliers, universities, or early teams that actually fit the question.
03
Shape field visits, feedback rooms, workshops, demo sessions, or partner conversations around real decisions.
04
Turn what happens in the room into a next-step map: deepen, pause, publish, partner, or expand.