Prompts are powerful, but they are also brittle. Manually handcrafted prompts often work well for a time, but when models or their weights change, performance degrades forcing developers back into a cycle of prompt tinkering. This trial-and-error process is laborious, unscalable, and costly to maintain. In this talk, we introduce the era of prompt optimization: what it is, how it works, and why it is essential for building scalable and reliable AI systems. We will explore current tools and techniques, with a focus on automated prompt optimization using DSPy and its family of optimizers, and review some of the latest research and approaches in the field. Attendees will gain a clear understanding of how prompt optimization transforms prompting from brittle craftsmanship into a robust, reproducible, and scientific workflow.

Shashi Jagtap is the Founder of Superagentic AI and a former Apple engineer. He is building the next-generation agentic AI stack from developer tools to orchestration, focused on evaluating, optimizing, and deploying full-stack, production-ready AI agents. He created SuperOptiX, an evaluation-first, optimization-core framework for agentic AI, designed to help companies accelerate their journey into agentic AI systems. Shashi also organizes the London Agentic AI Meetup and the London AI-Native Test Automation & DevOps Meetup, fostering community and knowledge-sharing in the fast-evolving AI ecosystem.