An AI-powered learning coach that integrates with Claude Code to accelerate skill mastery through spaced repetition and personalized syllabi.
Learn FASTER is an AI-powered learning coach that integrates with Claude Code to help developers master technical skills faster. It uses spaced repetition, personalized syllabi, and active practice to optimize learning based on science-backed principles like the FASTER framework. The tool generates exercises, schedules reviews, and tracks progress directly within your development environment.
Developers and technical learners who want structured, efficient ways to master new programming languages, frameworks, or prepare for certifications. It's ideal for self-directed learners using Claude Code.
Developers choose Learn FASTER for its seamless integration with Claude Code, personalized learning paths, and evidence-based techniques like spaced repetition and teach-back reinforcement. It transforms passive learning into active, retention-focused practice.
AI-powered learning coach with spaced repetition with Claude Code - master any knowledge faster with personalized syllabi and progress tracking
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Integrates directly with Claude Code via slash commands like `/learn` and `/review`, enabling in-IDE coaching as detailed in the usage section, eliminating context switching.
Built on the FASTER framework (Forget, Act, State, Teach, Enter, Review), incorporating spaced repetition and teach-back sessions proven to boost retention, as demonstrated in the demo.
Generates customized syllabi based on skill level and goals, with four modes (Balanced, Exam-Prep, Theory-Focused, Practical) for tailored coaching, adapting to different learning styles.
Includes auto-generated exercises and teach-back mechanisms that force active recall, shown in the demo where explaining concepts enhances retention 2-3x over passive reading.
Exclusively built for Claude Code, making it unusable with other IDEs or AI tools, as stated in the README, which limits flexibility for developers in diverse environments.
Requires specific prerequisites like uv package manager and Python 3.12+, and creates multiple directories and files on first run, which can be intrusive and time-consuming.
As a newer project, it lacks extensive community plugins, integrations, and documentation compared to established learning tools, with contributions still welcome per the README.