GoalStack

GoalStack is a productivity application designed for professionals pursuing certifications. Users can create certification goals with target dates, break them into study milestones, track daily progress, and manage study resources all in one place. This project is part of the 777-1 Experiment, built with a "goldilocks zone" prompt that is intentionally underspecified to test how AI models handle ambiguity. After initial generation, 7 context engineer subagents (Amber, Kristy, Micaela, Lindsay, Eesha, Daniella, and Cassandra) will review the application in sequence, each focusing on their specialized domain. The findings will be documented in a case study that contributes to developing an algorithm for predicting prompt failures before they happen. As a medium-complexity project with explicit authentication (signup/login required before any functionality), GoalStack tests how AI models handle upfront auth requirements and localStorage-based data persistence.