Cloud Wars Live with Bob Evans

In this AI Agent & Copilot Minute, Mason Siefert outlines how Microsoft’s latest enhancements to Copilot Studio — especially the new tools in the Power CAT Copilot Studio Kit — are designed to bring structure, governance, and measurable quality to enterprise-scale AI agents.

Key Takeaways

Rubrics refinement: The headline feature in the updated kit is the rubrics refinement tool, which addresses a growing challenge in agentic AI operations — how to consistently and accurately grade agent responses. The tool introduces a repeatable feedback loop where teams define evaluation rubrics, compare AI-generated grades with human evaluations, and then refine instructions when the two don’t align. The result is a more systematic, scalable way to ensure automated assessments meet human-level standards.

Governance & visibility: Beyond evaluation, the kit strengthens oversight across the AI estate. A new compliance hub automatically flags configuration risks to help teams stay ahead of governance concerns. Conversation KPIs allow organizations to track agent performance without manually reviewing transcripts, and an agent inventory provides a centralized view of custom agents and the capabilities they rely on. Together, these features bring operational clarity to expanding AI environments.

Looking ahead: As agentic systems scale, structured coordination between humans and AI will be critical. Tools like the rubrics refinement workflow signal a shift from experimentation to disciplined operations, where evaluation, compliance, and performance tracking are embedded into the lifecycle of every agent. Organizations that formalize these processes now will be better positioned to manage complexity and deliver trustworthy AI outcomes at scale.

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In today's Cloud Wars Minute, I explain why aligning your role with AI may be the key to thriving in the next 18 months.

Highlights

00:05 — There's a lot of discussion right now about the impact of AI on the job market. Microsoft AI CEO Mustafa Suleyman has weighed in on this debate regarding the pace of AI innovation and its impact on employment.

00:53 — “I think that we're going to have a human-level performance on most, if not all, professional tasks. So white-collar work, where you're sitting down at a computer, either being a lawyer or an accountant or a project manager or a marketing person — most of those tasks will be fully automated by an AI within the next 12 to 18 months.”

01:18 — "Many software engineers report that they're now using AI-assisted coding for the vast majority of their code production, which means that their role has shifted now to this meta function of debugging, scrutinizing, or doing strategic stuff like architecting, putting things into production."

01:36 — And he explains that this is a very different relationship with AI — one that's evolved a huge amount over the past six months — and things are moving fast. But you don't need to read this with doom and gloom. Focus on the second statement I read out instead.

01:52 — In that, Suleyman says roles have shifted, and that's the crux of achieving success in the AI Era — recognizing that things are changing and that, to keep up with these changes, you have to orient yourself alongside AI, to align your role to work with AI — not against it, not instead of it, but with it.

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Key Takeaways

SEO evolution: Most people prefer having answers given directly rather than searching for them, which is reshaping how information is accessed. As a result, Search Engine Optimization (SEO) is evolving toward AI-driven assistants and agents that deliver faster, more personalized responses than traditional web searches.

AEO & GEO: Two approaches emerging from this shift are Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO). AEO focuses on making content easier for AI engines to understand, while GEO aims to make that content the trusted source AI relies on when generating future responses.

Looking ahead: To implement AEO and GEO, teams need well-structured data and content that directly answers questions. While this is already visible in digital commerce, other sectors like finance will soon see AI engines compare products and assess risk using trusted data sources and trust scores.

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In today's Cloud Wars Minute, I explain why deep on-premises expertise is becoming a strategic advantage in the AI-driven cloud economy.

Highlights

00:03 — One of the things we're seeing here in early 2026, as so many things change around the tech industry and customer expectations, is that three old timers in the Cloud Wars Top 10 —Microsoft, SAP, and Oracle — for each company, 50% or more of its revenue comes from the cloud.

00:56 — So these are, in some ways, the graybeards, and some people have tried to position them as legacy companies, or ones that reflect the past and not the future. I think all three companies have done a fantastic job of moving into a very different sort of future. This legacy term that some people apply to them was initially meant as a put-down.

01:51 — They've got cloud expertise now, and these three companies, I think, are doing so well in the cloud in part because they understand the traditional landscape that their customers have operated in. Microsoft's total revenue for the quarter ended December 31: $81.3 billion. Of that, $51.5 billion in the cloud — that's 58%.

03:05 — So this idea of legacy, which was initially meant as a put-down, an insult, that dismissal of these companies — that's one of the silliest ideas that has come along in a long time. I think this also serves as an occasion for all of us to think about some terms and concepts that had a lot of currency in the past that might not in the future.

04:13 — We've got to look with fresh eyes, a fresh mindset about what's new, what's important, what isn't, and not carry forward the ideas or the models, the templates of the past into what's rapidly becoming a very, very different future. I’ve got a detailed article going into this and offer some more perspectives on this move.

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In this episode of the AI Agent & Copilot Podcast, John Siefert, CEO of Dynamic Communities and host of the podcast, is joined by Christopher Lochhead, bestselling author of "Play Bigger," to explore the shift from knowledge worker to “creator capitalist.” Lochhead previews his new book, "Creator Capitalist," which he will officially launch at the 2026 AI Agent & Copilot Summit NA in San Diego, outlining how AI and agents are transforming value creation, careers, and leadership in the modern economy.

Key Takeaway

From Knowledge Worker to Creator Capitalist: Lochhead explains that for decades, professionals operated as “knowledge workers,” where “knowledge is power” and execution defined success. But now, AI and agents are "making the value of existing knowledge closer to free every day.” He argues that professionals must shift upstream, focusing on identifying new problems and creating new value rather than executing within existing systems.

Execution Is No Longer the Differentiator: For years, leaders were told that “ideas are a dime a dozen” and that execution was everything. But Lochhead bluntly states, human beings "cannot out-execute a GPU.” As agents increasingly automate operational work, doubling down on efficiency won’t protect careers.

The Four Capitals Framework: Creator capitalists build a flywheel of four capitals: intellectual, relationship, reputational, and financial. Intellectual capital is your “different”— the differentiated insight and judgment you uniquely bring. Relationship capital determines whose calls get answered. Reputational capital is not a personal brand, but “an earned reputation for results.” Financial capital flows from creating massive value for others. Together, they compound into durable advantage.

Radical Responsibility in the AI Era: Lochhead stresses personal accountability: “If your career is a function of somebody else…you’re in trouble.” Waiting for an employer or title to define value is dangerous in a rapidly shifting environment. Instead, professionals must proactively design their trajectory, using AI as leverage to amplify their capabilities and create net-new value, rather than protect outdated roles.

Out-Creating the Machine: The defining insight of the episode: “You can’t out execute a GPU, but you can out-create one.” Siefert reinforces that curiosity, creativity, and critical thinking are not soft skills — they are survival skills. Those who embrace the creator capitalist mindset will not just adapt to AI disruption; they will become the most successful value creators in history.

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