Introduction
Welcome to Panday! This week marks the beginning of our journey to revolutionize how people navigate skilled trades careers. Our team came together with a shared vision: to create a platform that helps aspiring tradespeople find their path in an industry that desperately needs them. With 700,000+ skilled trades positions expected to open by 2028, we knew we had to build something meaningful.
Design Team Updates
Our design team hit the ground running this week! Reagan reorganized our Discord server to create a structured workspace and finished our initial user survey, awaiting feedback before distribution. Bruno took the lead on user research, setting up focus groups with trade students and developing comprehensive survey questions covering demographics, career experience, and apprenticeship backgrounds. Darrel contributed to the survey development, ensuring we're asking the right questions to understand our users' needs.
The team also began reaching out to trade students for future user research, laying the groundwork for authentic, user-centered design.
Development Team Updates
Our developers dove deep into the technical architecture this week. Nikita created documentation for Git and Docker local development workflows and validated the concept by interviewing three people in trades. Ozem researched vector embedding databases, exploring MongoDB Atlas and Neon's pgvector extension, while also downloading Xcode to explore mobile app possibilities.
Josh began exploring Model Context Protocol Servers for organizing trade school training, certifications, and apprenticeship programs. Peter analyzed the SkilledTradesBC electrician construction website, identifying it as a valuable data source for our platform.
TL;DR
Week 1 was all about foundations: organizing our team structure, initiating user research, and exploring technical architectures for vector embeddings and data sources. We're building the infrastructure that will support Panday's mission to guide people through skilled trades careers.
What's Next?
Next week, we'll dive deeper into RAG (Retrieval-Augmented Generation) implementation, finalize and distribute our user survey, and begin prototyping our core features. The technical team will focus on embedding models and database architecture, while design continues gathering user insights.