Optimizing Large AI Conversation Sessions with a Session Distiller
The author built a 'session distiller' to reduce the size of large AI conversation logs by selectively trimming tool results and screenshots, while preserving the full conversation text.
Why it matters
Optimizing the size of AI conversation logs is important for maintaining performance and avoiding context loss as sessions grow longer.
Key Points
- 1Large AI conversation sessions can become bloated with tool outputs and screenshots, slowing down the conversation
- 2The session distiller keeps the full conversation text but applies rules to trim tool results based on type (e.g. keep only first/last lines of Bash outputs)
- 3This reduces the session size by 90% on average, from 70MB to 7MB, without losing any critical context
Details
The author had a 4-hour coding session with the AI assistant Claude, which resulted in a 73MB session file. This file contained a lot of extraneous data like tool outputs, file previews, and screenshots that were no longer relevant. To address this, the author built a 'session distiller' that reads the session log, preserves the full conversation text, and applies deterministic rules to selectively trim the tool results based on type (e.g. keeping only the first and last 5 lines of Bash outputs, or a 200-char preview of file edits). This approach avoids the risk of an AI-based summarization losing important details. The key technical challenge was mapping tool results back to their originating tool calls, which was solved by building a lookup table. The end result is a 90% reduction in session size, from 70MB down to 7MB, without losing any critical context.
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