Perform 2026 felt like a turning point for Dynatrace, and when Steve Tack joined me for his fourth appearance on the show, it was clear this wasn’t business as usual.
We started off with a little Perform nostalgia, from Dave Anderson’s unforgettable “Full Stack Baby” moment to AI Rick’s debut on the keynote stage. But the humor soon gave way to substance. Because beneath the spectacle, Dynatrace introduced something that signals a broader shift in observability: Dynatrace Intelligence.
Steve was candid about the problem they wanted to solve. Too much focus on processing data. Too much time spent sewing tools together. Too many dashboards. Too many warnings. The real opportunity, he argued, is turning telemetry into trusted, automated action. And that means combining deterministic AI with agentic systems in a way that companies can actually trust.
We have unpacked what this looks like in practice. From United Airlines using a digital cockpit to improve operational performance, to TELUS and Vodafone demonstrating measurable ROI on stage, Perform’s focus was firmly on production results rather than pilot projects. As Steve put it, the industry has been in “pilot purgatory” long enough. The next phase requires real-world implementation and real returns.
A large part of that trust comes from the foundation that Dynatrace has laid with Grail and Smartscape. By combining unified telemetry in its data lakehouse with real-time topology mapping and causal AI, Dynatrace is positioning itself as the engine behind explainable, reliable automation. When hyperscaler agents from AWS, Azure, or Google Cloud call Dynatrace Intelligence, they are expected to get answers based on causal context rather than probabilistic guesswork.
We also explored what this means for developers, who often bear the burden of nimbleness and fragmented tools. New integrations in VS Code, Slack, Atlassian, and ServiceNow aim to bring observability directly into developer workflows. The goal is simple in theory and complex in execution: keep engineers in their flow, reduce work, and enhance human decision-making rather than replace it.
Naturally, autonomy raises questions about risks. Steve acknowledged that people will remain closely monitored for now, with most interactions between officers still requiring checkpoints. But as trust grows, so does the willingness to let systems automatically optimize themselves, heal themselves and resolve problems automatically.
We finished by zooming out. In a market saturated with AI claims, Steve encouraged listeners to bet on change rather than stick with the status quo. There will be hype. There will be an officer wash. But real value also emerges for those willing to experiment, learn, and scale responsibly.
If you want to understand where AI observability is going, and how deterministic and agentic intelligence can coexist within business operations, this episode provides a grounded, practical perspective straight from the Perform show floor.
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