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This article focuses on engineering AI agents as structured software by introducing an intermediate protocol layer for versioning and encapsulation within enterprise environments like Walmart. It addresses critical challenges in production deployment, specifically regarding data exfiltration risks through runtime taint tracking and dynamic schema projection rather than treating language models merely as chat interfaces. The discussion centers on transforming agentic workflows from chaotic loops into reliable, maintainable systems using standardized tool protocols such as MCP.
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Presentation: From Copy-Paste to Composition: Building Agents Like Real Software

InfoQ40 min de cititArticolul și perspectiva sunt în engleză.

Jake Mannix discusses moving AI agents past chaotic "1970s BASIC" architectures. He shares how implementing an intermediate protocol layer allows engineering leaders to build versioned, encapsulated "virtual tools." This design enables interface mapping, dynamic schema projection, and runtime taint tracking to proactively eliminate data exfiltration risks without slowing velocity. By Jake Mannix

Jake Mannix: I'm Jake, another member of the Fellows community from Walmart. My colleague Aditya talked a bunch about agents. We work together all the time. We both are dealing with agents, because we're working on the agentic middleware that powers a lot of stuff at Walmart for the 20,000-something software developers and data scientists that are building agents like crazy right now. We're nearly done with the year of agents, but we're mostly software engineers in here. Let's talk about what it's actually like to build an LLM-based agent. To clarify specifically in the language Aditya was talking about, very much more abstract in the notion of LLM in a loop. We'll talk specifically around LLM-based agents at large enterprises, and if we're going to be software engineers, how do we actually build them like actual programs that we're used to building and running. First off, I want to ask a couple questions. How many of you have run an AI agent in production of any kind? How many of you have written your own MCP tool, not use someone else's server, but written a tool for MCP use of some kind? How many of you have connected those…

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