I am a Technical Product Manager and Systems Thinker. I specialize in computational systems, algorithmic design, and co-architecting software platforms to scale efficiently while reducing operational overhead. I also hold an honors background in Engineering Science (NUS), specializing in Computational Engineering.
A curated mirror of the custom spaces, functional engines, and interactive software shipped by J-Labs Space.
Events memories space, compiled
A high-performance media environment designed to allow wedding couples, event hosts, and families to share photos seamlessly and create centralized memory storage zones without platform performance overhead.
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Marathon preparation, simplified
A responsive algorithmic planner enabling endurance athletes to set customized macro target paths, map training loads, and receive individualized daily prep blueprints cleanly.
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Communicating workflows, simplified
A fast vector canvas environment structured specifically for cross-functional teams to chart spatial data logic, draw complex technical workflows, and translate functional goals visually.
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Size the market. Price the product. Ship the plan.
A specialized analyst workspace that converts product briefs into structured go-to-market strategies on demand. It programmatically maps out TAM/SAM/SOM target segments, models unit economics, recommends pricing strategies, and outlines competitive landscapes module by module.
Real-world PM workflows transformed via custom AI agents and autonomous pipeline integrations.
Automated changelogs to stakeholder comms
After each development sprint, this autonomous agent analyzes completed task tickets, extracts technical release notes, and generates a formatted, value-driven summary. It automatically distributes highlights into company announcement threads to help marketing and GTM teams cleanly translate engineering progress into positioning messaging.
Algorithmic triage & automated follow-ups
Managing high-volume incoming feature requests often results in scoping delays. This agent processes each ticket under the specific context of Terrascope's product landscape. It flags ambiguities, drafts localized clarification questions, tags the request creator directly, and triggers immediate feedback loops to save hours of manual triage time.
RAG-driven knowledgebase deflection
To mitigate repetitive queries from internal business teams, this RAG (Retrieval-Augmented Generation) agent hooks directly into product documentation and internal wikis. It dynamically replies to stakeholder questions on Slack, deflecting common inquiries and protecting focus blocks for deep product management work.