What makes an AI agent effective: a better model, the right tools, specialized skills, more context, subagents, or a verification loop? In this interactive talk, every audience member receives a limited budget and bids in a live auction for the components needed to assemble an agent harness. Participants then lock in their chosen combination and watch it enter a controlled benchmark gauntlet measuring correctness, regressions, safe execution, speed, and cost until only the winning harness remains.Through the results, we will explore which components materially improve an agent, which merely add cost and complexity, and why the system surrounding an LLM can matter as much as the model itself.
Martin Brian is a Senior AI Engineer specializing in the design, deployment, and operation of agentic systems in demanding production environments. At Marvik, he works as part of the AI team for a global payments platform, building agents that automate end-to-end software-development workflows across the organization.
