Enhancing AI agents with long-term memory: Insights into LangMem SDK, Memobase and the A-MEM Framework

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More AI agents can automate many tasks that enterprises want to perform. One downside, though, is that they tend to be forgetful. Without long-term memory, agents must either finish a task in a single session or be constantly re-prompted. So, as enterprises continue to explore use cases for AI agents and how to implement them safely, the companies enabling development of agents must consider how to make them less forgetful. Long-term memory will make agents much more valuable in a workflow, able to remember instructions even for complex tasks that require several turns to complete. Manvinder Singh, VP of AI product management at Redis, told VentureBeat that memory makes agents more robust. “Agentic memory is crucial for enhancing [agents’] efficiency and capabilities since LLMs are inherently stateless — they don’t remember things like prompts, responses or chat ... Read full article.