AI agents are becoming one of the biggest topics in enterprise technology, but there is a critical challenge many organizations are still overlooking: context.

In this conversation, I speak with Massimo Merlo from Elastic about why context engineering is becoming essential for the next phase of enterprise AI. We explore why powerful AI models are not enough on their own, why real-time enterprise data matters, and how businesses can make AI systems more useful, reliable and secure.

We also discuss the debate around AI agents and the future of enterprise software. Will agents abstract away traditional software, or is the real story about where value is moving in the technology stack? As AI becomes more embedded in workflows, search, retrieval, observability, governance and data infrastructure all become increasingly important.

See how Elastic makes context engineering possible at https://www.elastic.co/elasticsearch/context-engineering #sponsored 

In this interview, we cover:

🤖 The current state of enterprise AI
📊 Why many organizations are still stuck in pilots and demos
🧠 What context engineering means in simple business terms
🔎 Why search, retrieval and real-time data are critical for AI agents
🔐 How context helps make AI more reliable, secure and governed
🚀 What leaders should do now to prepare for the future of enterprise AI

If you are interested in enterprise AI, AI agents, generative AI, data strategy, AI governance, context engineering or the future of business technology, this conversation offers a practical look at what comes next.

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