Introduction
Week 11 pushed the boundaries of what Panday's AI can do. We designed a Relationship Context Recognition system to make conversations progressively more intelligent, though implementation proved challenging. We also made strategic decisions about mobile development.
Development Team Updates
Ozem made a strategic pivot in mobile development, switching from native Swift to Expo. The reason? Apple's $120 developer fee just to test apps isn't worth it at this stage. Expo provides cross-platform development (iOS and Android) without the upfront costs, making it perfect for our prototype phase. He set up the panday-native repository and began development.
Josh attempted to implement Relationship Context Recognition (RCR), an advanced AI memory system that would: track complete conversation threads and topic progression, build dynamic models of each user's expertise level, adapt explanation depth based on demonstrated knowledge, and connect related concepts across conversations. While the RCR implementation didn't succeed this week, the research and design work laid important groundwork for future iterations. Josh also worked on the landing page and made the AI chatbot collapsible to improve screen real estate management.
TL;DR
We pivoted mobile development to Expo for cost-effectiveness and cross-platform support. Advanced AI memory systems (RCR) were designed but proved too complex for immediate implementation. The landing page and chatbot UI received improvements.
What's Next?
Week 12 will focus on connecting the mobile app to our production database, completing the landing page, and finalizing features for our final presentation.