Rethinking how we Scaffold AI Agents - Rahul Sengottuvelu, Ramp

The author, Rahul Sengottuvelu, shares insights from his experience working with large language models (LLMs) and how they have evolved from early stages to present-day AI agents. He discusses the challenges faced with earlier models, the importance of building scalable systems that improve with more compute, and the practical applications at Ramp, a finance platform. Sengottuvelu exemplifies the development of agents using a CSV parsing task and explores how AI can significantly enhance backend systems. He also presents a futuristic approach where LLMs could potentially act as backends, showcasing a live demo of an AI-driven email client.