Month: 2026-03 — Focused on delivering a scalable instructor workflow in Artemis to support adaptive learning and better interactivity. Delivered a multi-step plan capable workflow that orchestrates competencies and exercises via interconnected sub-agents, with enhanced chat responses including embedded preview data.

In February 2026, delivered a new feature in ls1intum/Artemis: Bidirectional Competency Mappings for Instructors, enabling instructors to create two-way mappings between competencies to enhance adaptive learning and competency management. The feature leverages companion interaction workflows to map competencies, improving personalization and alignment with course outcomes. The work center is the core commit that introduced the functionality and reflects strong cross-team collaboration to drive measurable instructor tooling improvements.

January 2026 highlights Artemis (ls1intum/Artemis): Delivered Interactive AI-assisted competency creation and management. Implemented a multi-agent orchestration system that enables instructors to interactively create and manage competencies via a dedicated AI assistant, with a sub-agent handling targeted tasks to improve efficiency and user experience in competency management. The work includes the commit 8dd51cbbab796d40080058e3e4bdc76c29e5a51b, "Adaptive learning: Allow instructors to improve competency creation through companion interaction (#11944)". Impact: Improves instructor efficiency, accelerates competency design, and enables adaptive learning workflows at scale; reduces manual overhead and positions Artemis for broader AI-assisted capabilities. Bugs fixed: No major bugs reported or required fixes this month; release prioritized feature delivery and stability. Technologies/skills demonstrated: AI-assisted workflows, multi-agent orchestration, sub-agent task delegation, UX improvements for competency management, integration within the Artemis codebase; evidence of commit-driven development.

Monthly summary for December 2025 (ls1intum/Artemis). This month focused on delivering a performance-oriented enhancement for the Artemis chat feature, integrating a Shared Chat Client Performance Optimization with Memory Advisor. The change retains conversation context efficiently and tunes chat client configuration to improve responsiveness under real workloads.

November 2025 monthly summary for ls1intum/Artemis focused on delivering core features for the Atlas AI integration and enhancing conversation history handling.

October 2025 monthly summary: Delivered key features across edutelligence and Artemis that strengthen content structure, enable AI-assisted competency management, and enhance instructor workflows. Focused on business value by enabling structured competency-to-exercise mappings, scalable AI assistants, and user-friendly interfaces. Notable outcomes include improved content connectivity via Weaviate, automated competency creation with Atlas Companion, and AI-guided instructional support, backed by REST endpoints and feature toggles to support safe rollout.

July 2025 — Artemis (ls1intum/Artemis): Delivered Instructor Average Progress by Learning Path feature to empower instructors with data-driven insights. This involved introducing a new AverageProgressDTO, adding repository support to fetch learning paths, implementing a service to compute the average, exposing a REST endpoint, and updating the frontend to display the metric. No major bugs fixed this month. The work enhances course analytics, enabling targeted interventions and better monitoring of student engagement by learning path. Key technologies: Java/Spring Boot backend (DTOs, repository, service, REST), REST API design, frontend integration, and data modeling for progress analytics. Commit reference: b44b545b1d5bf397dba40b3bca6eed5cae025484.