Welcome to Our Takes on AI

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