Beyond grep: The case for a context-rich AI coding harness
The article explores the shift in AI development from focusing solely on large language models to building 'harnesses' that manage context and model interaction. Industry experts argue that lean, adaptable software layers are essential for maximizing the utility of rapidly evolving AI models.
Why it matters
As AI coding tools become more prevalent, the architecture of the software managing these models will determine how effectively developers can integrate AI into complex codebases.
Agentic Development Beyond grep: The case for a context-rich AI coding harness Augment Code’s Vinay Perneti talks models, harnesses, and context.
4 Vinay Perneti, VP of Engineering at Augment Code, speaks during a presentation. Credit: Augment Code Vinay Perneti, VP of Engineering at Augment Code, speaks during a presentation. Credit: Augment Code Text settings Story text Size Small Standard Large Width * Standard Wide Links Standard Orange * Subscribers only Learn more Minimize to nav
There are a lot of AI coding applications out there, and as impressive as large language models and the agents they enable have become, many of the most recent developments in AI-assisted development have been in the software that manages those models, not just the models themselves.
Earlier this summer, I spoke with the head of product for Claude Code, Anthropic’s Cat Wu, about that company’s approach to building that software.
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