Oren Michaels, founder of Barndoor.ai and expert in AI governance, delves into the pivotal role of AI agents in the workplace. He explains how AI agents differ from tools like ChatGPT and stresses the necessity of governance alongside innovation. Oren warns about the risks of unsanctioned Model Context Protocol (MCP) usage, highlighting its impact on security. He shares insights on treating AI agents like eager interns, revealing real-world successes in sectors like finance and marketing. This conversation serves as a guide for executives aiming to embrace responsible AI integration.
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insights INSIGHT
Agents Act; Chat Interfaces Advise
Agents act rather than only suggest actions, creating a larger potential blast radius than chat interfaces.
Treat agents like enthusiastic interns who need context, supervision, and gradual authority increases.
volunteer_activism ADVICE
Watch Agents’ Actions, Then Approve
Monitor agent actions in real time and compare attempted actions to expected behaviors before allowing writes.
Block or investigate attempts that fall outside expected context or role boundaries.
volunteer_activism ADVICE
Map Roles, Then Narrow Agent Scope
Map human role permissions into agent permissions but make the agent's scope a strict subset of the human's access.
Further limit agent capabilities by task, system, and trust level to reduce risk.
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Chris Daigle sits down with Oren Michaels, founder of Barndoor.ai, to explore the rise of AI agents in the workplace and why governance and security matter just as much as innovation. From defining what makes an AI agent different from ChatGPT, to tackling the risks of the new Model Context Protocol (MCP), Oren explains how executives can unlock real productivity gains while avoiding costly mistakes.
You will hear how to treat agents like eager interns with guardrails, where companies are already seeing ROI in finance, marketing, and contracts, and why shadow AI and unsanctioned MCP use could be your biggest risks. Packed with real-world AI applications and executive-level strategy, this episode is a playbook for business leaders ready to adopt agents responsibly.
Model Context Protocol (MCP) for agent-to-system integration
📌 Chapters
00:00 – Intro to Oren Michaels and Barn Door AI 02:20 – From APIs to AI agents: lessons from enterprise adoption 06:46 – Defining an AI agent vs. ChatGPT and automation 13:25 – Why agents lack conscience and what that means for business 18:10 – Governance frameworks for AI agents 22:58 – Risks and opportunities of the Model Context Protocol (MCP) 27:19 – Who inside companies is owning AI governance 33:25 – Enterprise scale vs. mid-market AI adoption 38:36 – Real-world wins in finance, marketing, and contracts 42:53 – The difference between automation, RPA, and agents 46:28 – Shadow AI, unsanctioned MCP, and risk management 50:56 – Where to learn more about Barn Door AI
Episode tags:
AI in the workplace, AI for business leaders, Generative AI at work, Non-technical AI leadership, Real-world AI applications, Workplace AI adoption, Executive AI training, AI productivity tools, AI transformation stories, Ethical AI business, AI implementation guide, AI strategy for executives