How to build agents with filesystems and bash
Vercel shares a technique for building agents that use filesystem and bash tools instead of custom tooling. This approach simplifies agent design, reduces costs (e.g., sales call summarization dropped from $1.00 to $0.25 per call on Claude Opus), and improves output quality by letting models leverage their native understanding of code navigation patterns.
Many of us have built complex tooling to feed our agents the right information. It's brittle because we're guessing what the model needs instead of letting it find what it needs. We've found a simpler approach. We replaced most of the custom tooling in our internal agents with a filesystem tool and a bash tool. Our sales call summarization agent went from ~$1.00 to ~$0.25 per call on Claude Opus 4.5, and the output quality improved. , our text-to-SQL agent.We used the same approach for d0
The idea behind this is that LLMs have been trained on massive amounts of code. They've spent countless hours navigating directories, grepping through files, and managing state across complex codebases. If agents excel at filesystem operations for code, they'll excel at filesystem operations for anything. Agents already understand filesystems.
Customer support tickets, sales call transcripts, CRM data, conversation history. Structure it as files, give the agent bash, and the model brings the same capabilities it uses for code navigation.
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