In a real production environment, AI agents do not need to be impressive. They need to be useful, predictable, and easy to reason about when something goes wrong.

In this session, I will share a lightweight AI agent system I use every day at work. It is based on practical patterns learned from building and operating AI-assisted workflows in a professional setting, under real constraints like time, reliability, and team expectations.

Instead of focusing on full autonomy or complex orchestration, this approach emphasizes clear agent roles, controlled autonomy, and keeping a human in the loop at the right points. I will walk through how the system is structured, the types of daily tasks it supports, and why lightweight agent designs have worked better in real-world development and decision-making.

The talk focuses on practical concerns that matter in everyday work. These include deciding which tasks are worth turning into agents, designing agent behavior that stays safe and predictable, and integrating agents into existing workflows without disrupting productivity. The session is framework-agnostic and based on real usage, so attendees can apply the ideas directly in their own environments.