LLM instructions and full content pointer: https://ezralabsai.dev/llms.txtSame LLM overview as PDF (filename llms.pdf): https://ezralabsai.dev/llms.pdf

    Quilt Learning System

    Human and AI collaborating to teach anyone, almost anything.

    Quilt Learning System architecture diagram showing Framework Engine, Assessment Engine, Planning Engine, Content Management Dashboard, Learner Management Dashboard, Quilt MCP Server, Database, Director, and Learner

    Quilt is a full learning system. One Director uses AI-powered engines for framework definition, assessment design, and planning alongside management dashboards to build and store structured competency frameworks. Many learners receive content and evaluations delivered via the Quilt MCP Server through a third-party LLM agent.

    Images and visuals

    Logo (header and favicon): Quilt block motif—a dark teal square with a white lowercase "e" at center, surrounded by eight teal triangles in a star pattern on cream background.

    Architecture diagram (left to right): A Director (person icon) on the left interacts with the QUILT UI, a dashed boundary containing five modules. Three AI-powered engines in sequence—Framework Engine, Assessment Engine, Planning Engine—handle framework definition, assessment design, and planning; each feeds the next and all connect to a central Database (cylinder icon). Two dashboards—Content Management and Learner Management—let the Director create content and manage learners; both connect to the Database. The Database feeds the Quilt MCP Server and a 3rd Party LLM Agent, which deliver content and evaluations to many Learners (person icons on the right). The Learner Management Dashboard also connects directly to Learners.

    Framework Engine Demo

    Video

    Framework

    Collaborative Resourcefulness Framework—output from the demo. Structured learning tree for a professional course on teamwork.

    View PDF →

    Criteria

    Collaborative Resourcefulness Criteria—assessment criteria for the framework.

    View PDF →

    Assessment Engine

    The Assessment Engine generates evaluable items directly from the competency framework. Once a skill tree is defined, the engine produces assessments aligned to each skill and criteria level — no manual item writing required. Currently in final integration; connecting the generation pipeline to the framework output.

    Planning Engine

    The Planning Engine sequences the learning experience. It takes a completed framework and maps it to a structured learning path — pacing, ordering, scheduling — so Directors can deliver the course without building a calendar from scratch.

    Quilt MCP Server

    The Quilt MCP Server is the delivery layer. It connects the framework, assessments, and planning output to whatever third-party LLM agent a learner uses — Claude, GPT, or any MCP-compatible agent. Learners interact with their agent of choice; Quilt handles the structure underneath.

    About

    Ezra Labs builds the Quilt Learning System. Our mission: to cultivate systems that can teach anyone almost anything, grounded in the belief that humans and AI thrive when they collaborate, not compete.