Enhancing AI agents with long-term memory: Insights into LangMem SDK, Memobase and the A-MEM Framework
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Summary
As AI agents become increasingly ubiquitous in the workplace, the need for long-term memory to enable complex tasks to be completed in a single session is growing.
Memory allows AI agents to recall past interactions and maintain context to deliver more personalised responses and gain autonomy, says Manvinder Singh, VP of AI product management at Redis, however, decisions also need to be made on what the agents need to forget to ensure AI systems maintain speed, scalability and flexibility.
Companies like LangChain, Memobase, and OpenAI’s Swarm are beginning to offer long-term memory options for agents to help enterprises plan for deployment at scale.
Thoughtworks’ Mike Mason said memory transforms AI agents from simple, reactive tools into dynamic, adaptive assistants, limiting their ability to improve interactions over time without it.