DESIGN FOR LIFE

Agents Must Earn Autonomy: Lessons from Salesforce Agentforce and MuleSoft Episode summary At Dreamforce 2026, Salesforce put deterministic control at the center of its agent strategy. Rather than trusting AI models to make every call, Agentforce now pairs LLM reasoning with scripted workflows and hard rules, while MuleSoft’s governance layer enforces identity, tool permissions, and rogue agent detection at the gateway. Brian, Campbell, and Michael explore what this shift me

Have We Solved the AI Agent Oversight Issue? NVIDIA announced its Open Agent Safety Platform the morning we recorded. It's an open-source runtime (OpenShell) plus a hardware watchdog (Sentry) designed to limit what AI agents can do and quarantine them when they go beyond their boundaries. More than 100 organizations signed on, including Anthropic, SAP, Microsoft, IBM, and Salesforce. So is agent oversight solved? The three of us don't agree. 🔹 Take 1: The conversation finall

Should We Let AI Vendors Shift The Responsibility to Their Users This weekend, the CEOs of Anthropic, OpenAI, Meta, and xAI all issued public statements calling for AI development to slow down. In this episode, Brian Silverman, Campbell Robertson, and Michael Muhlfelder push back on the framing itself, arguing that the "slow down" conversation is obscuring a more urgent and more solvable problem: governance. The core argument: Models don't act until prompted. The risk isn't a

Fired Then Rehired at 30% Raise Podcast Episode 22: AI Deployment Is Everywhere. Results Are Still Missing. Adoption isn't the problem anymore, nearly every organization has some form of AI in production. The problem is that almost none of them can point to a measurable return on it. In this episode, Michael, Campbell, and Brian dig into why the gap between deployment and results keeps widening, and what that means for how businesses should be evaluating AI investment going f

AI Train, leaving the station! Your AI Just Broke the Law, Good Thing It Was Only Testing, or Was It? Three Takes on AI — Episode 19 Three frontier labs, Anthropic, OpenAI, and now Meta have all disclosed incidents of their AI models going rogue during testing. Congress's answer is the AI Kill Switch Act, co-sponsored by Rep. Ted Lieu and Rep. Nathaniel Moran. In this episode, Brian Silverman, Campbell Robertson, and Mike Muhlfelder ask the question the bill never quite gets

Students Used AI to Score 96% on their exams How Would Your Organization Score on its use of AI? Stop Blaming Shadow AI. Start Harvesting It. A professor at Brown University sent his midterm home. Nearly every student scored 96% or above. He called it cheating. What actually happened A Professor at Brown University, who has taught the course for nearly two decades, said enrollment for the semester was unusually high, jumping from a typical range of 8 to 30 students up to 86.

Beyond the AI Strategy: The Risks Your Board Is Missing Most organizations are now developing an AI strategy. Many have approved pilot programs, invested in new tools, and begun exploring how artificial intelligence can improve productivity, customer experience, and business performance. But approving an AI strategy is not the same as understanding the risks behind it. In this episode of Three Takes on AI, Brian Silverman, Campbell Robertson, and Michael Muhlfelder begin with

AI spend is projected to hit $2.52 trillion by the end of 2026, yet more than half of CEOs report seeing no measurable value from their investment. In this episode of Three Takes on AI, Brian Silverman, Campbell Robertson, and Mike Muhlfelder unpack why that gap exists, and why most of the conversation around AI ROI is asking the wrong question. The discussion centers on a familiar pattern: organizations leading with technology instead of business outcomes, measuring AI again

What happens when the limits of AI tools are not really technical — but human? In this episode of Three Takes on AI, Brian, Campbell, and Mike talk through the AI tools they are actually using, where those tools are helping, and where they still fall short. From ChatGPT, Claude, Gemini, and Perplexity to image generation, workflow automation, coding, research, and productivity, the conversation gets practical fast. But this episode is really about judgment. AI can summarize,

Humans vs. AI? You're Asking the Wrong Question "The question isn't whether AI will replace humans. The question is where humans create value when AI becomes part of the process." For years, the conversation around artificial intelligence has been framed as a competition: humans versus machines. But what if that's the wrong debate? In this episode of Three Takes on AI, Brian, Mike, and Campbell explore a more nuanced question: how do humans and AI work together to create valu

Three Takes on AI: Data Centers vs. Drinking Water Artificial intelligence is changing nearly every industry on the planet, from healthcare and finance to education, entertainment, and national security. But behind every AI breakthrough is a growing network of massive data centers consuming staggering amounts of electricity and water. In this episode of Three Takes on AI, the hosts tackle one of the most important and least discussed questions surrounding the future of AI: W

Three Takes on AI | Star Trek, Terminators & The Battle Over Ungoverned AI What does Elon Musk's courtroom testimony have to do with a deleted database, a rental car company, and the starship Enterprise? More than you'd think. In this episode of Three Takes on AI, Brian Silverman, Michael Muhlfelder, and Campbell Robertson dig into one of the most pressing questions in tech today: are we heading toward a Star Trek future where AI serves humanity, or a Terminator scenario wher

Click Image to view Podcast The "Standard" AI Governance framework is a myth. In this episode, we break down why the market is currently "bolstering its ignorance" and what real risk management looks like in the age of Agentic AI. Episode Overview Is your organization buying "meaningless boxes"? Today, Mike, Campbell, and Brian pull back the curtain on the state of AI Governance. We start with a reveal of Campbell’s satirical "Governance Topology", a complex diagram filled wi

👉 “ The AI Champion Paradox: Are You Automating Yourself Out of a Job? AI is supposed to make us more efficient. It’s supposed to remove repetitive work, unlock productivity, and help organizations move faster. But there’s a question most people aren’t asking: What happens when the AI you helped build… replaces you? Across industries, people are actively training systems, improving workflows, and driving AI adoption inside their organizations. And in many cases, those same e

In a world where AI is everywhere, the conversation is usually about how to use it more. This episode takes a different approach. In Three Takes on AI , we explore the limits of AI, and the often-overlooked moments where using it can actually lead to worse outcomes. From weakening critical thinking to over-automation and misplaced trust, we unpack the real risks that come with relying too heavily on AI tools. Through candid discussion and practical examples, we highlight wher

What happens when AI makes a decision that impacts someone’s life, who is responsible? What happens when AI makes mistakes in a company? Wrong prices? Missed Deliveries? Or miss diagnosed patient? In this episode of Three Takes on AI, Brian, Mike, and Campbell explore the growing question of accountability in an AI-driven world. From healthcare decisions to business automation, the discussion dives into whether responsibility lies with the technology, the companies deployin

Artificial intelligence is transforming how businesses operate, from generative AI tools that create content in seconds to AI-powered automation that streamlines operations. But as AI adoption accelerates across industries, one critical question remains: Where does human judgment still matter? In this episode of Three Takes on AI , we explore the real-world limits of artificial intelligence in business. While AI can analyze data, generate recommendations, and increase efficie

Human vs. AI Intelligence We continue to describe AI in terms of human intelligence: when it will reach AGI or ASI, or how it “hallucinates” when it makes mistakes. But does this way of thinking actually help us understand ,AIor does it create more confusion? Mike, Campbell, and Brian tackle this question head-on. Does anthropomorphizing AI benefit humans, or does it distort how we think about what AI really is and how it should be used? Mike takes the position that AI is e

AI is already being used across organizations, often quietly, informally, and without oversight. In this episode of Three Takes on AI , Brian, Mike, and Campbell dig into the reality of Shadow AI : why it’s happening, what it signals about leadership and culture, and how organizations should respond. Rather than framing Shadow AI as a compliance failure, the conversation reframes it as a symptom of unmet demand . Employees are experimenting with AI to move faster, solve probl

In this episode of Three Takes on AI , we explore why 2026 is shaping up to be a crossroads moment for Agentic AI. From emerging frameworks and standards to real-world successes, failures, and governance challenges, we discuss what it will take for agentic systems to move beyond demos and deliver real business value. Most importantly, we examine the evolving role of humans, not as obstacles to automation, but as essential supervisors of AI in a world defined by ambiguity, t