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A developer built kaeru, an open-source shared memory system for AI agents that allows them to persist context across sessions, share knowledge between different agents and humans, and visualize memory as a 3D galaxy. The tool supports multiple agent frameworks and includes features like time-travel, importance levels, and reasoning trails.
Built a competitive-intel MCP server that returns only sourced data to prevent AI agents from fabricating competitor numbers.
An analysis of why running more than three parallel agents in Claude Code hits a bottleneck, revealing a duty-cycle problem where the developer becomes the primary latency source, and the 'join' process of merging parallel outputs is the biggest time cost.