Founder Fail Tales Vol. 6

What does it take for AI systems to truly understand code and what happens when software is no longer designed only for humans, but for AI agents too? Join Munich🥨NLP and JetBrains for an evening exploring Code Intelligence and AI Agents, bringing together research and industry perspectives on how LLMs understand program behavior and how humans and coding agents can collaborate on software development. Talk 1: Code World Models Tobias Lindenbauer · JetBrains Research Talk 2: Designing Software for Humans and Agents Artem Kislovskiy · Artefact Two talks, pizza, drinks & snacks, and plenty of time to connect with Munich’s NLP, AI, and developer community. 📅 Agenda 17:45 | Doors open 18:20 | Pizza arrives 🍕 18:50 | Welcome & Intro JetBrains × Munich🥨NLP 19:00 | Talk 1: “Code World Models” Speaker: Tobias Lindenbauer · JetBrains Research Abstract Modern LLMs perform well at generating code that solves a given task, but they may introduce regressions elsewhere in the codebase, or simply write code with poor runtime or memory performance. This has led researchers to investigate how well LLMs model program behavior internally: Can they tell whether a test passes or fails without running it? Do they have a feel for which parts of the code to target to robustly optimize runtime or memory? In this talk, Tobias will outline the emerging Code World Models research direction and share early findings from an ongoing project at JetBrains Research. About the Speaker Tobias Lindenbauer is a Research Engineer at JetBrains Research working on Code World Models for improved LLM code understanding. Previously, he worked on context management, LLM routing, memory systems, and benchmarks, resulting in publications at DL4C@NeurIPS and REALM@ACL. 19:40–19:50 | Short break 19:50 | Talk 2: “Designing Software for Humans and Agents” Speaker: Artem Kislovskiy · Artefact Abstract One coding agent writes; another challenges. In this live demo, Claude Code and Codex share a split terminal in an ac

TUM Social AI Demo Day - Second Edition 🚀 Eight teams. Eight social-impact projects. One semester of building, testing and turning ideas into real solutions. On October 13, we’re bringing everything together at CHECK24 HQ in Munich for the second edition of the TUM Social AI Demo Day - our biggest showcase of the semester. At TUM Social AI, students from different disciplines work together with NGOs, social organizations and industry partners to explore how AI can be used for real-world social challenges. Over the course of the semester, our teams work directly with their partners to understand a problem, develop a solution and turn it into something tangible. Demo Day is where that work comes to life. This semester, eight teams will take the stage to present what they have built covering challenges in humanitarian aid, education, integration, access to opportunities and more. Watch the teams pitch live, hear feedback from our jury, meet the people behind the projects and stay afterwards for drinks and networking at CHECK24. The Projects wahl.chat - an LLM-powered platform for political dialogue action medeor - AI-driven procurement to speed up humanitarian aid delivery UN Women - research on gender bias in large language models Aflatoun - multilingual AI support for educators worldwide Kulturator - improving access to funding opportunities in Germany Entreculturas - automated receipt processing for NGO financial operations InitiativGruppe - a chatbot connecting newcomers in Munich with language courses and local resources Kolping × AWS - a digital companion for vocational success Each team will have 5 minutes to pitch their project, followed by 5 minutes of live feedback from the jury. It’s not only about the presentations. Demo Day is also a chance to meet our project teams, NGO partners, students from across Munich, and people from the AI and tech ecosystem. And if you’re curious about joining TUM Social AI yourself, come talk to us - we’ll also be happy to tell

The PAL-E training is a hands-on workshop teaching managers and other leaders how to best support, guide and coach their teams .

Wir laden dich gemeinsam mit der "Datamonster e.V. Regionalgruppe Bayern" herzlich zu unserem nächsten Meetup vor Ort in München ein! Willkommen ist jede:r, der/die Lust auf einen offenen Austausch hat, ganz gleich wie erfahren du bist, welche Technologien du präferierst oder was dein Spezialgebiet ist. Talk 1: Zero to Fabric App: Automatisierte Legacy-Code-Transformation mit Rayfin. (André Ebert) Fabric ist die neue ganzheitliche Datenplattform in deinem Unternehmen und du stehst vor unzähligen bestehenden Berichten, Auswertungen und Dashboards in verschiedenen Notebooks und Repositories, die besser schon seit gestern migriert sind. In dieser Hands-on-Session machen wir genau das: Wir transformieren die Inhalte bestehender Repositories in sofort einsatzbereite Microsoft Fabric Apps – von Grund auf. Wir betrachten zunächst verschiedene Arten von Source-Repositories, um vorhandenen Code mithilfe von typischen Frontier-Modellen zu transformieren. Rayfin kümmert sich dann um das Project-Scaffolding, leitet das SQL-Schema ab und deployt das Ergebnis direkt als Fabric App in Azure. Talk 2: Warum „SQL Server oder Microsoft Fabric?” die falsche Frage ist. (Erik Esmaty) SQL Server oder Microsoft Fabric? Das ist die falsche Frage. Erfolgreiche Datenplattformen setzen heute nicht auf eine einzelne Technologie, sondern auf die richtige Kombination aus beiden. In dieser Session betrachten wir praxisnahe Architekturmuster, die SQL Server, Azure SQL und Microsoft Fabric für Analytics, KI und Governance miteinander verbinden. Anhand realer Szenarien zeige ich, wo die jeweiligen Stärken liegen, wie die Plattformen zusammenspielen und wie eine zukunftssichere Modernisierungsstrategie ohne vollständige Migration aussehen kann. Folgende ungefähre Agenda erwartet dich: ab 18 Uhr Ankommen 18:30 Uhr 1. Vortrag & Fragen 19:15 Uhr Pause mit Essen & Gesprächen 19:45 Uhr 2. Vortrag & Fragen 20:30 Uhr Abschluss und Zeit für weitere Gespräche Das Meetup findet in deutscher Sprache