Learn more about upcoming Events
Agent Tracing & Debugging, Framework Benchmarking
AI agents deliver value, but decisions are hard to inspect. When results fail, teams struggle to see what broke and why—raising risk and slowing engineering. This session makes behavior transparent with observability and tracing: end-to-end runs, tool calls, prompts, tokens, latency, cost, errors, plus benchmarking.
Beyond the IDE: How different Stakeholder Perspectives Shape
As AI coding assistants like GitHub Copilot spread, organizations face a variety of challenges and opportunities in integrating these tools into their development workflows. This roundtable explores perspectives from governance, legal, and engineering leaders on adopting agentic coding AI.
Roundtable: Industrial R&D Reinvented
This roundtable explores how integrating AI agents can revolutionize the product lifecycle, from concepts and customer requests to commercialization, with insights and strategic perspectives on how autonomous systems enable a seamless, intelligent, accelerated path to market in the era of AI-driven engineering.
Ecosystem Meetup: AI@Scale&pace
Our March Meetup will center on the key success drivers for AI adoption in 2026. We will focus on best practices for scaling AI in enterprises at speed and scale, considering the global context for 2026 and as well as other crucial aspects top of mind. The agenda will be published end of January.
AI & Data Sovereignty: From Legal Blocker to Business Enabler
In an era where AI and data-driven business set the pace, sovereign control over one’s data is a decisive competitive factor. Meanwhile, legal and security challenges grow. This event highlights data sovereignty and offers practical solutions for businesses.
From Idea to Productive AI Case
Here participants learn a pragmatic way to turn an AI idea into a production-ready use case plan. We focus on framing, measurable value, feasibility and risk checks, prioritization, and a path to MVP and production—including make-or-buy. Participants leave with an AI Use Case Canvas one-pager and clear next steps.
Beyond the operative toolbox: Architecting your no-code/low-code
No-Code/Low-Code platforms can accelerate automation and AI-enabled workflows - often faster than traditional delivery cycles. But the real challenge starts when organizations scale beyond a few isolated automations: decisions around where NC/LC fits, what it should run, and how to manage risk become critical.
AgentOps Working Group 2026: Data-Knowledge and Risk Management
This Working Group brings together leading technical and governance experts to define the engineering and operational practices required to develop, deploy, and monitor agentic AI systems in production safely and at scale. The focus is on translating risk theory into actionable engineering and governance practice.
