Solving the Relevancy Problem: Using Your Data in Models

Human–AI Interaction: Where Do Humans End and Machines Begin?

Prompting, context, agents, interfaces — the way humans and machines interact is being rewritten. Ed Anuff and Anant Jhingran talk with Kate Blair of IBM Research about what’s broken in today’s AI experiences, why collaboration is missing, and how the next generation of agentic interfaces could redefine the boundary between people and AI.🚀 Explore the playbook powering enterprise AI → https://dtsx.io/4dPdAAEOpen research projects mentioned:https://beeai.dev/https://mellea.ai/____________________

Rethinking Developer Productivity in the AI Era

Developer productivity is changing fast — and 🤖 AI is at the center of it.🎙️ On this episode of Context Window, Ed Anuff and Anant Jhingran open with their take on the biggest AI headlines, then sit down with 💡 Neel Sundaresan, GM of Automation & AI at IBM.They cover:⏳ Where developers really lose time📈 How AI is moving beyond code💰 What token costs mean for your budget🤔 Whether one model can do it allThe episode wraps with Ed and Anant’s 🗣️ unfiltered takeaways and 🔮 predictions for the future of dev work.

MCP-ization and GraphQL: Enabling AI-Driven Open Data Access

Join IBM’s Ed Anuff (VP, Langflow and Open Platform Strategy), Anant Jhingran (CTO, IBM Software), and Roy Derks (Principal Product Manager, IBM) to explore MCP-ization and GraphQL. They will discuss how Model Context Protocol (MCP)—an emerging open standard that “standardizes how LLMs interface with external systems”—intersects with GraphQL to revolutionize open data access and API integration. The session will feature a live demo by Roy, showcasing how to MCP-ize a GraphQL API for AI-driven data access.

Solving the Relevancy Problem: Using Your Data in Models

AI hallucinations. Stalled RAG pilots. Inaccurate answers. Let’s talk about the real reason behind those challenges: your data. In this episode of Context Window, DataStax CPO Ed Anuff [https://www.linkedin.com/in/edanuff/] and IBM CTO of Software Anant Jhingran [https://www.linkedin.com/in/anantjhingran/] unpack the relevancy problem—why enterprise AI apps struggle to produce useful results, and what you can do about it. From unstructured data and dynamic query generation to reasoning, reranking, and beyond, we’ll cover what it actually takes to move from pilot to production. Don’t miss this practical, no-hype session on making AI work right now.

Building the Infrastructure for Agentic AI

In this special episode of Context Window, recorded live at IBM Think, DataStax CPO Ed Anuff joins IBM’s Anant Jhingran for a candid conversation on the future of enterprise AI. They dive into: – The rise of AI agents as the new application layer – Why clean APIs and model orchestration matter – The economics of tokens in production AI – How enterprises can move from GenAI hype to real impact Whether you’re a CIO, architect, or tech leader, this is essential viewing for navigating the next wave of AI.