Planning a virtual workshop? I’m sharing my top tips to help you run it successfully! Voltage Control has been hosting multiple virtual workshops a week…
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Planning a virtual workshop? I’m sharing my top tips to help you run it successfully! Voltage Control has been hosting multiple virtual workshops a week…
Voltage Control's Virtual Work Guide is an applicable curation of the best tools and processes every facilitator and team leader needs to conduct successful remote work.
A great meeting can set the tone for weeks of productive work while a boring one can steal all the momentum from a team. This…
The apps and virtual design thinking exercises you need to run a successful remote workshop.
We wanted to give the community an opportunity to come together to learn and practice virtual decision-making methods and tools.
Right now, if you’re not working in a hospital, grocery store, pharmacy, or other essential business, you’re likely working from home as best as you…
The unknowns of COVID-19 pose a concern for how to continue business as usual and many facilitators have found themselves wondering how to navigate this…
In this episode of the New Friction podcast, host Douglas Ferguson speaks with Peter Bell, founder of Gather.dev and author of the forthcoming O’Reilly book Scaling AI Adoption in Engineering. Bell draws on his work running invite-only peer communities for senior engineering leaders to diagnose why most organizations stall out in AI pilot mode rather than achieving meaningful transformation. The conversation maps three distinct patterns of engineer resistance—skeptics burned by early models, craft-focused developers who resist the shift toward managing agents, and those with principled objections to AI—and offers concrete tactics for reaching each group. Bell and Ferguson explore how AI amplifies existing organizational health: strong DevOps practices compound upward while process debt scales its dysfunction. They examine the mandate trap, measurement via token usage as a diagnostic rather than a performance metric, and the non-negotiable role of psychological safety in any serious adoption effort. The episode closes with Bell’s call for engineering leaders to build hands-on with current models, arguing that firsthand intuition—not secondhand reports from a VP of AI—is what this transition demands.
In this episode of the New Friction podcast, host Douglas Ferguson speaks with Jeff Grabill, Dean of the College of Arts and Sciences at the University at Buffalo, recorded in the immediate aftermath of the IHE US AI Summit 2026, which both men attended. Grabill recounts what emerged from that two-day working convening: the foundation of the Buffalo Statement, a collective public agenda for AI in higher education, and reflects on why the room's patience, grounded confidence, and willingness to question prior assumptions exceeded his expectations. The conversation explores why universities, often criticized for moving slowly, may possess exactly the right instincts for AI transformation: designing conversations intentionally, engineering productive friction, and moving fast and slow at the same time. Ferguson and Grabill dig into how AI has relocated rather than eliminated friction, particularly in learning environments, where effortless output now threatens the productive struggle that actually builds expertise and ideas. They close on a librarian's insight from the summit — "I don't care if AI created it, I care if it's true" — and Grabill's call for businesses and universities to actively seek one another out as partners in working through this moment.
AI is quietly reshaping the workforce in ways most leaders aren’t measuring. While concerns often focus on entry-level job loss, the bigger risk is the erosion of apprenticeship and skill development. Drawing on research from Cornell, MIT, Yale, Microsoft, and real-world examples from organizations adopting generative AI, this article explores how “AI chains” remove the learning experiences that turn juniors into future experts. Learn why experience starvation threatens leadership pipelines, how hidden AI adoption creates governance blind spots, and what organizations can do to preserve mentorship, judgment, and long-term capability while still capturing AI-driven productivity gains.