Loadout Tool Lets Developers Carry AI Coding Agent Context Across Projects

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A developer built an open-source tool called Loadout to solve the recurring problem of manually recreating AI coding agent configuration files every time a new project or environment is opened. Loadout acts as an adaptive context engine that detects the current working environment — such as a Rust, Next.js, or Python repo — and automatically injects the appropriate user-defined context into the agent. Unlike project-level files such as CLAUDE.md or AGENTS.md, Loadout stores personal workflow preferences and coding conventions in local, gitignored overlays, leaving shared team configurations untouched. Context is built from reusable fragments that can be mixed across different loadouts, avoiding duplication. The tool also supports six standardized workflow stages — explore, brainstorm, plan, implement, verify, and ship — so developers can maintain consistent engineering processes even when switching between different AI coding agents.

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