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Modern AIOps: What It Takes to Build Reliable AI Products

Explore episode Jun 5, 2026

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What Is an AI Engineer? Context Engineering vs. Prompt Engineering

At 20:30 · chapter starts 19:55

Jesse surfaces a debate that's live across the industry: what exactly is an AI engineer, and how is it different from an ML engineer or a regular software engineer? Karthik sidesteps the label-policing and focuses on the skills that actually matter. Staying current as the field moves rapidly under your feet is table stakes. But the deeper competency is context engineering — the deliberate craft of deciding what information to feed a model, in what quantity, and at what point in the reasoning chain. Frameworks like LangChain, Vercel AI SDK, and Mastra help, but they don't solve the subjective, use-case-specific judgment calls. Beyond context, architecture choices dominate: do you use a single reasoning model with all tools available, or a planner-executor setup where one model reasons and another acts? Two years into the mainstream AI era, Karthik admits nobody has the definitive answers. The right architecture is deeply context-dependent, which is itself part of what makes this such a rich engineering problem.

Technology
What Is an AI Engineer? Context Engineering Beats Prompt Engineering

Modern AIOps: What It Takes to Build Reliable AI Products · Jun 5, 2026 Technology

An AI engineer isn't just someone who writes good prompts. The more important skill is context engineering — knowing precisely how much information to feed a model, when to feed it, and how to structure it. Beyond that, AI engineers must constantly choose between single-agent and multi-agent architectures, with no established right answer yet.

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