Building an AI agent is only the beginning. The real challenge starts after deployment, when every prompt adjustment risks fixing one issue while quietly introducing ten more. The difference between an agent that appears to perform well and one that consistently delivers the right outcomes lies in rigorous evaluation, continuous monitoring, and disciplined refinement. Learn how to move beyond intuition, confidently measure the impact of every change, and continuously improve AI agents with production-ready reliability. 

Discover how to accelerate the development of intelligent, conversational AI applications with Google's latest Genkit Agents API.  Learn how developers can simplify the complexity of building agentic, full-stack applications by combining conversation management, tool orchestration, state persistence, streaming, and frontend integration into a unified framework. Explore practical approaches for creating scalable, production-ready AI experiences with support for multi-agent workflows, human approval, and long-running tasks. 

アジア最大級の保険会社 AIA Group は、業務の 90% をクラウド・コンピューティングに移行することによる、ビジネスアプローチのモダナイズを検討していました。この目標をサポートするため、AIA は Red Hat® Ansible® Automation Platform を使用して、セキュリティとコンプライアンスを改善するとともに、手動によるプロビジョニングプロセスを排除しました。その結果、同社はプロビジョニング時間を 6 カ月からわずか 1 時間に短縮し、サービスの市場投入時間を改善することができました。現在では、23,000 人以上の従業員がセルフサービスのプロセスや開発環境へのアクセスを活用し、革新的な新サービスの創造に貢献できるようになりました。

Washington Health Benefit Exchange operates Healthplanfinder, an online insurance marketplace used by one in four state residents to find, compare, and enroll in coverage. To accommodate massive, rapid growth during the COVID-19 pandemic, the organization sought to replace its complex existing infrastructure with an integrated, microservices-based architecture. Working with Red Hat and Deloitte, the organization adopted Red Hat OpenShift to take advantage of iterative scalability on its private cloud. The team also used Red Hat Application F...