Want to scale AI agents without breaking anything? Retrieval engineering is the answer.
AI agents are multiplying as corporations adopt the technology in record numbers. Smarter underlying models, better tool use, and improved The post Want to scale AI agents without breaking anything? Retrieval engineering is the answer. appeared first on The New Stack .
As corporations increasingly adopt AI agents in production environments, the underlying infrastructure is struggling to keep pace. With smarter models, better tool use, and improved multi-agent collaboration, AI agents are evolving from impressive demos to practical technology. However, the challenges of ensuring fresh, relevant, and quickly available information for these agents are becoming more pronounced.
The issue lies in the retrieval architecture that provides AI agents with the necessary information. As companies deploy more agents and tasks, the system is subjected to waves of queries, leading to concurrency issues and making it difficult to ensure that the AI-legible information remains current and readily available. Whit Walters, Field CTO and Lead Analyst at GigaOm, and Bonnie Chase, Director of Product Marketing at Vespa.ai, will discuss these challenges and potential solutions in a live conversation on September 24 at 12 p.m. Eastern/9 a.m. Pacific.
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