aiqbench analysis
This presentation addresses the critical need for robust architectural foundations in AI agent development, moving beyond fleeting hype toward scalable engineering practices like modular frameworks and process science integration. It offers actionable guidance for leaders aiming to build resilient systems that can handle unpredictable cross-functional demands without repeating historical mistakes in agent design. The core message emphasizes terraforming legacy environments into event-sourced artifacts capable of sustaining long-term operational viability as the field matures from early experimentation to production reality.
Presentation: From Hype to Strong Foundations: What the Rise, Fall and Resurgence of Agents Can Teach Us About Outlasting the Cycle

Aditya Kumarakrishnan explains how to move past the "amnesia phase" of AI. He shares a blueprint for engineering leaders to build modular agent frameworks using CoALA, leverage decades of process science for scalable workflows, and "terraform" legacy environments into robust, event-sourced artifacts capable of handling unpredictable, cross-functional agent demands. By Aditya Kumarakrishnan
Aditya Kumarakrishnan: I'm Aditya Kumarakrishnan. I'm a technical fellow at Walmart Global Tech. I'm here to talk to you about Agents: The Missing Manual. Part of this talk is an experience report. Part of it is theory. It's essentially about how we're thinking about fundamentals as we build agents. An interesting observation I've had over the last two years building agents is how looking back at ideas can feel like you're looking into the future. I'm here to talk to you about four big ideas that are actually from the past, but today they feel like they'd be something from the future. I'm a huge AI agent bull. The bull case is that I think agents are inevitable. What I mean by inevitable is that the conceptual idea of an agent is an inevitability. That doesn't mean that the realization of them is inevitable. What I find is that we're in the amnesia phase of building agents. We're building them on shaky foundations. We're making meandering progress. We're recommitting mistakes and relearning lessons from previous cycles of building agents. I want to spend most of the talk really telling you about four big ideas we should all be thinking about…
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