In this episode of Operationally Intelligent, Ricardo Castro explores why so many platform teams fail by building tools nobody asked for. He breaks down the ivory tower mentality that plagues platform engineering, the importance of sitting with developers to understand their real pain points, and how operational data should drive every decision. Ricardo and Adam discuss why DevOps, SRE, and platform engineering aren't competing disciplines, how metrics like lead time for change and developer satisfaction can bridge the gap between engineering and leadership, and why treating internal tools as products is the key to adoption. The conversation makes a compelling case that observability is the thread connecting it all.

In this conversation, Karthik Kalyanaraman, Co-Founder and CTO of Langtrace, discusses the evolution and importance of observability in AI, particularly for large language models. He shares insights on the challenges faced by developers in implementing observability, the role of OpenTelemetry, and the significance of standards in preventing vendor lock-in. Karthik emphasizes the need for organizations to connect observability to business outcomes and the future potential of AI observability in building trust among engineering teams and executives.

In this episode of Operationally Intelligent, Adam Kinniburgh and Michael Hausenblas discuss the nuances of operational intelligence and observability, exploring the importance of learning from incidents, the challenges organizations face in transitioning to operational intelligence, and the role of culture in fostering a supportive environment. They also delve into cost considerations, data storage strategies, and the potential of AI in enhancing operational intelligence practices.