Engineering self-improving AI systems

Please also register through the official AWS link here, as AWS Builder Loft requires it for entry. Without AWS registration, guests may not be allowed in. Overview AI agents are no longer a side experiment inside AI teams. They are becoming part of product surfaces, internal operations, customer workflows, developer tools, and decision-making systems. The question now is not just how to build an agent. It is how to build the harness around it: the systems, workflows, boundaries, infrastructure, and human decisions that decide what the agent can do, where it should stop, how it should recover, and how it gets better after real use. This room brings together builders working on that layer. Session Description We’ll spend the evening with engineers, founders, AI teams, cloud builders, and product teams who are designing what sits around agents once they become part of real systems. We’ll talk about closing the loop, what comes after the first working agent, how teams are thinking about agent systems in practice, and what builders are learning from real deployments. Agenda 5:00 PM — Check-in, food, and networking 5:30 PM — Welcome and room framing 5:40 PM — AWS technical segment on agentic AI and Amazon Bedrock 6:00 PM — Closing the Loop: Engineering Self-Improving AI Systems Nikhil Pareek, Founder of Future AGI 6:30 PM — Guest speaker sessions Two 15-minute talks from builders in the AI agent ecosystem. If interested in speaking/sponsoring, reach out to Vrinda 7:00 PM — Builder demos 5-minute demos from teams building agents, workflows, devtools, infrastructure, voice systems, or applied AI products. Interested in pitching? Submit here 8:00 PM — Open networking 8:30 PM — Close Building something relevant to AI agents, workflows, infrastructure, voice, devtools, or applied AI? We’re opening a few spots for guest speakers, 5-minute builder demos, and aligned sponsors. For any queries, feel free to reach out to here: https://www.linkedin.com/in/vrinda-damani/ About Future AGI Future AGI is an open-source end-to-end agent engineering and optimization platform that makes AI agents self-improve. It gives teams one place to simulate edge cases before launch, evaluate what actually happens in production, protect users from unsafe outputs in real time, and turn every trace into signal for the next version. Everything runs on one platform and one feedback loop, from first prototype to production.