Kern Promises Local Code Intelligence to Cut AI Token Costs by Up to 80%

A new open-source tool called kern, built in pure Go, aims to reduce the token overhead incurred when using AI coding assistants such as Claude Code, Cursor, and Codex. Rather than feeding entire codebases into large language models, kern uses AST-based parsing to deliver surgical context slices estimated at 500–2,500 tokens per query, compared to much larger conventional approaches. The tool operates as a single self-contained binary with local-first, zero-telemetry architecture that masks PII and credentials before any data reaches an LLM. A comparison with rival tools Graphify and Code Review Graph positions kern as better suited for active daily development, while the others remain preferable for multimodal documentation and CI/PR risk scoring respectively. Kern is available on GitHub under the handle JayveerPrajapati/kern and supports installation on macOS, Linux, and Windows.
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