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Darryll Colthrust

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Building AI Agents from First Principles at GoDaddy Everyone’s talking about AI agents lately, and for good reason. But at GoDaddy, we’re going deeper: starting from first principles to explore what makes an agent truly robust and usable in real-world scenarios. Instead of asking “What can we build fast?” we’re asking “What design choices make agents flexible, testable, and reliable long term?” Core Concepts • Tool-centric design: everything an agent does is a tool call, with precise APIs and granularity. • Decision vs. delivery: agents decide what to do; tools handle how to do it—keeping systems modular. • Structured outputs & reflection: LLMs output both the tool call and the reason behind it, making debugging and iteration easier. • Universal tools: even user interactions (inform, confirm, request) are abstracted as tools, clarifying boundaries between logic and interface. Real-world use cases → Not just theory ✅Routing and responding to support messages ✅Surfacing emerging trends in sales data ✅Automating scheduling, inventory, or operations orchestration What we learned • Treating everything as a tool makes systems more predictable and extensible • LLM “verbosity” is valuable—it reveals reasoning and speeds iteration • Separating decision from execution reduces fragility and simplifies updates We’re still at the beginning, but these principles give us a strong foundation. As agents evolve, architectural clarity matters more than chasing the latest framework. 👉 Curious about architecture patterns that scale? Dive in here: Building AI Agents at GoDaddy: An Experiment in First Principles https://www.godaddy.com/resources/news/building-ai-agents-at-godaddy-an-experiment-in-first-principles
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