ThoughtDAG's Session Atlas Turns Local AI Agent Logs into Editable Graph Mirrors

ThoughtDAG has launched Session Atlas, a desktop feature that imports local AI agent sessions from tools like Codex and Claude Code into editable graph-based mirrors grouped by project. Unlike conventional agent memory systems, Atlas maintains a strict separation between the original session record, the user's curated workspace, and the context sent to future model requests. The original session file is never modified; users can edit, reorganize, or annotate mirrored nodes independently without altering the source history. Atlas also monitors active local sessions and incrementally appends new turns, respecting user edits and avoiding overwrites. The tool aims to give users explicit, transparent control over what context their AI agents receive, rather than relying on automatic or hidden memory retrieval.
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