Malong Technology
码隆科技
Senior Product Manager
For education AI and hardware-software systems, I owned product planning, algorithm requirements and evaluation, customer conversations, and commercial delivery — moving multiple product lines from solution design into real school use.
- 01AI product planning:
Owned planning for the AI Learning Space, lab AI assessment, and AI Smart Classroom — scenario breakdown, multi-surface architecture, and version roadmap.
- 02Algorithm requirements & evaluation:
Turned computer vision, large models, agents, RAG, and memory into product requirements, evaluation methods, human-AI collaboration, and acceptance criteria.
- 03Customer & commercial delivery:
Worked directly with schools and education authorities on research, solution presentations, public-class validation, and pre-sales, coordinating algorithm, engineering, hardware, and implementation teams through launch.
★ RECOGNITIONPerformance reviews were rated excellent throughout the role.
PROJECT EVIDENCE
Project evidence
These cases show planning, evaluation, and delivery across self-directed learning, AI assessment, and classroom products.
AI Learning Space
When content and school conditions were still incomplete, turn agents, learning terminals, and school operations into a self-directed learning loop that can be used every day
For secondary-school self-directed learning on campus, an AI companion agent connects learning terminals, course and practice content, a teacher console, and a school platform — giving students self-study, in-the-moment tutoring, and personalized practice, then turning that process into records teachers can review and respond to.
- My role
- Core product owner — Planned the student terminal, teacher console, school platform, booking kiosk, and display wall into a multi-surface architecture covering learning, teaching, and space operations
- Capabilities
- Agent product design · Multi-surface architecture · AI evaluation & behavior limits · Pilot and scaled delivery
- Why it mattered
- The product is in daily use at 10+ schools in Shenzhen, producing real student learning sessions and learning hours
Lab AI Assessment
Tender specs are only the entry ticket. Expand exam hardware into daily teaching and practice, then shift competition to scalable multimodal AI
For city-level physics, chemistry, and biology lab teaching and exam digitization — covering tender parameters, hardware-software terminals, exam operations, daily teaching, student practice, AI scoring, and human review. The product work was not stacking features, but judging, at each competitive stage, which variable would actually move the solution.
- My role
- Product planning and solution evolution — In policy-driven tender competition, judged that meeting specs is only the entry ticket; the real question is how schools keep getting value after they buy
- Capabilities
- Tenders & delivery · Scenario expansion · Multimodal AI · High-reliability evaluation
- Why it mattered
- The solution covers exams, daily teaching, and student practice, supporting regional teaching-and-exam programs and multi-school delivery
AI Smart Classroom
Turn a one-lesson demo into a deliverable class loop; then connect it with the AI Learning Space for preview and catch-up — without merging them into one app
For in-school classroom teaching — covering lesson building, AI-generated or reused class resources, student-terminal learning and interaction, live teacher monitoring, and after-class review. The product work is not a slide player. It is turning one class into a teaching process a school can run and trace, and planning data connections with the AI Learning Space for pre-class preview and after-class catch-up.
- My role
- Product planning and solution owner — Abstracted a standard product from multi-school classroom demos, defined an MVP loop of pre-class building, in-class monitoring, and after-class review, and drove it to a deliverable Beta
- Capabilities
- Classroom loop · Structured generation · Class snapshots & permissions · Cross-system data connection
- Why it mattered
- Formed a deliverable Beta: teacher lesson building, class-module generation, student-terminal learning, in-class tasks/quizzes, teacher progress views, and class-data archiving
