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In this episode, the AI hosts unpack the growing tension between AI hype and real-world adoption in software delivery.
While AI is advancing rapidly, many leaders focus on bold claims, like replacing entire teams, without grounding them in metrics that matter. Leaders find it challenging to determine the right metrics to measure the impact of AI, as well as the success of AI adoption and investments. I challenge this narrative and explore how frameworks like Flow Metrics and developer sentiment can help teams measure AI’s actual impact on speed, quality, and effectiveness.
Instead of chasing vanity metrics or using AI as a shortcut to cut headcount, we explore how it can expand capacity and elevate team performance when applied with intention.
Link to the article: Leading Through the AI Hype in R&D, originally published July 27, 2025.
Connect with me on LinkedIn
By Phil ClarkIn this episode, the AI hosts unpack the growing tension between AI hype and real-world adoption in software delivery.
While AI is advancing rapidly, many leaders focus on bold claims, like replacing entire teams, without grounding them in metrics that matter. Leaders find it challenging to determine the right metrics to measure the impact of AI, as well as the success of AI adoption and investments. I challenge this narrative and explore how frameworks like Flow Metrics and developer sentiment can help teams measure AI’s actual impact on speed, quality, and effectiveness.
Instead of chasing vanity metrics or using AI as a shortcut to cut headcount, we explore how it can expand capacity and elevate team performance when applied with intention.
Link to the article: Leading Through the AI Hype in R&D, originally published July 27, 2025.
Connect with me on LinkedIn