#memory
4 articles exploring memory. Expert insights and analysis from our editorial team.
Articles
How AI Agents Remember: Memory Architectures That Work
AI agents use four distinct memory tiers—working, episodic, semantic, and procedural—stored across context windows, vector databases, knowledge graphs, and model weights. Choosing the right architecture determines whether your agent stays coherent across sessions or forgets everything the moment a conversation ends.
Rowboat: The Open-Source AI Coworker That Actually Remembers
Rowboat is an open-source AI coworker with persistent memory that builds a knowledge graph from your work data. Unlike proprietary alternatives, it stores everything locally as plain Markdown, giving you full control over your AI assistant while maintaining long-term context across meetings, emails, and projects.
Memory: The Missing Piece in AI Agents
Why memory is the critical bottleneck in AI agent architecture, how RAG and vector databases solve part of the problem, and where the field is heading next.
AI Coworkers Are Here: Building Persistent Memory Into Your Agents
Discover how to build AI coworkers with persistent memory using RAG, vector databases, and context compression—the architecture powering the next generation of autonomous agents.