Ankush Rastogi

This talk addresses the "100-tool agent trap," where providing an AI agent with access to a vast number of tools simultaneously degrades its performance. As the tool catalog grows, agents become slower, more expensive, and less accurate, often confusing similar tools or inventing new ones. The core thesis is that this issue stems from forcing the model to process an entire catalog on every request, leading to context overload and decision-making difficulties.