The field of AI Engineering is evolving from simple 1:1 applications to complex, AI-intensive systems with high LLM-call ratios. This talk explores the search for a 'Standard Model' for AI engineering, analogous to MVC or ETL in traditional software, proposing several candidates including LLM OS, LLM SDLC, and a new SPADE (Sync, Plan, Analyze, Deliver, Evaluate) model for building robust applications.
Paul van der Boor and Zulkuf Genc from Prosus discuss the practical realities of deploying AI agents in production. They cover their in-house evaluation framework, strategies for navigating the GPU market, the importance of fine-tuning over building from scratch, and how they use AI to analyze usage patterns in a privacy-preserving manner.
Authors James Phoenix and Mike Taylor discuss the evolution of prompt engineering from a creative art to a rigorous engineering discipline. They cover the core principles of prompting, the importance of programmatic evaluation, the role of agents, and how to manage application lifecycles as models evolve.