Beyond the Model: What Makes Coding Agents Actually Work

The article argues that effective coding agents like Claude Code succeed not primarily because of the underlying LLM model, but because of the surrounding system architecture—including tool integration, memory management, repository context, and prompt caching. This reframes AI development productivity: it's not just about having a more powerful model, but about intelligent system design around that model. Understanding these components is crucial for anyone building or evaluating AI-assisted coding tools, as the engineering of the agent harness often matters as much as the model itself.