The author details the construction of a web search agent, inspired by Perplexity, which aims to decide when to search the web mid-answer and provide cited sources. The agent was built using a Bun backend, React 19 frontend, Tavily for search, and OpenRouter for the language model. After initial success, the author reflected on the definition of an "agent harness," distinguishing it from a simple script by the code that manages tool use and context, rather than the model itself. The implemented system features a looping mechanism where the model decides to use tools, context is managed by trimming messages, and output is a structured event stream, confirming it as a functional, albeit single-tool, harness. AI
IMPACT Provides a practical example of building an agentic harness, highlighting the distinction between a script and a true agent.
RANK_REASON Developer describes building a specific AI-powered tool and reflects on its technical definition.
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