Why AI Coding Agents Forget Everything Between Sessions and How to Fix It

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A developer writing on DEV Community observed that AI coding agents reset completely between chat sessions, retaining none of the corrections or standards communicated in previous conversations. Unlike human colleagues who carry feedback forward, agents begin each new session from a blank state, forcing the developer to repeat the same instructions repeatedly. Attempts to fix the issue by rephrasing or front-loading instructions proved ineffective because the real problem was where corrections were stored, not how they were worded. The developer found that embedding instructions into persistent files the agent reads at session start — rather than relying on chat history — was the only reliable way to maintain consistent behavior. This approach, which the author links to frameworks called FARE and BARE, addressed coding style consistency but still left gaps around task sequencing and self-review by the agent.

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