Why Your AI Agent Behaves Differently in Production
A workshop for engineers, PMs, and founders building LLM-powered products, with a practical focus on reliability, evaluation, and production-level performance.
AI agents are moving from demos into real product workflows. But once agents are used in production, the challenge is no longer just “is it reliable?”
We stress-tested 8 frontier models against the same adversarial inputs. The best model blocked 91% of attacks. The worst blocked 53%. Same prompts, same setup. After optimization, both converged above 95%.
Security is one reliability factor. The same optimization loop applies to accuracy, tool use, and workflow consistency.
The harder questions are:
How do we know if an agent is actually reliable?
How do we measure whether a prompt, workflow, or tool-use change improved performance?
How do we debug failures across multi-step agent behavior?
How do we move beyond one-off prompt fixes and build a repeatable improvement loop?
We’ll share practical ideas and a demo of MEGA Code. The goal is to have a real builder-focused discussion about what it takes to make AI agents more measurable, reliable, and production-ready.
What to expect:
5:30 - 6:00: Arrival, Pizza, Drinks, Networking
6:00 - 6:30: Talk – From Prompt Fixes to Production-Level Agent Reliability
6:30 - 7:00: Demo – Evaluating and Optimizing AI Agent Behavior with MEGA
7:00 - 7:15: Setup / Guide – How to Start Measuring Agent Performance
7:15 - 8:00: Q&A, Open Discussion, Networking
Pizza and beverages will be provided.
Save your spot, spaces are limited.
Venue graciously provided by KIC Silicon Valley.
About the Organizer:
MEGA helps teams evaluate agent behavior, identify failure patterns, optimize prompts and workflows, and use evidence from each run to improve future performance. Our goal is to help builders move from one-off agent experiments to reliable, measurable, production-ready AI products.