Team

TopStack

Project Concept

TopStack is a personal data platform that transforms fragmented lifelogs (journal entries, personal notes, long-running audio transcriptions, daily summaries from AI-connected wearables (i.e. Limitless Pendant, Omi, Meta Smart Glasses, etc) into a cohesive, searchable memory archive with integrated relationship management.

The platform is designed to be source-agnostic, enabling future integration with photos (Synology, Apple), calendar events, and manual journal entries. For the MVP, we focus on Limitless Pendant as the primary data source, building a generalized schema that supports multi-source ingestion with it’s agentic loop driven by OpenClaw (or alternative agentic orchestrator).

Entry

Status: Not Started

Team Roster

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XelaXander Joo Team Lead RSVP Approved

Founder and Chief Builder at XSLabs

XelaXander is a seasoned technologist with a strong passion for innovation and problem-solving. Currently serving as a Founder and Master Builder at XSLabs. With a 16 year background in the technology industry (Meta, Google, Microsoft, Academic/eng research labs) and a electrical engineering degree (with heavy doses of CS and BioE) from the University of Illinois at Urbana-Champaign, Xander's career reflects their dedication to tech developmpent and integration for real world impact. Their skills in technology and problem-solving make them a valuable asset in any project they undertake, demonstrating a commitment to excellence and creativity in the field.

Technology, innovation, problem-solving, AI engineering, application development

Currently, XelaXander is working as a Founder and Chief Builder (Eng) at XSLabs, focusing on AI agentic systems development, applying intelligence and technology to enable superhuman capabilities, lifestyles, and play!

Jegosh John RSVP Approved

Software Engineer at AAPL

deepdiffs.com - The name captures how I work and think: I chase depth—probing complex systems from AI to everyday dilemmas—and I value the tiny, relative diffs that turn blank editors into robust software and half-formed notions into lasting insights. “Deep” nods to layered AI architectures and a habit of asking why until the roots of a problem show—an exploration mindset that prefers first principles over surface fixes. “