Podcast #6 Agentic AI Systems

Episode 6: AI Agents—Beyond the Workflow

AI agents are here, and they’re changing the game. Loren Horsager joins Angela Schultz to demystify how agentic systems work—and why they matter right now. From memory and context to voice interfaces and team collaboration, this episode lays the groundwork for using agents strategically.

You’ll learn:
- Why 2025 is “The Year of the Agent”
- How to get started with agents—even without coding
- Real-world use cases from research to operations
- The difference between tools that talk and tools that think

Listen Here:

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Episode 6 – AI Agents: From Workflow to Intelligence

In Episode 6 of *The Conversation*, Angela Schultz (Curriculum Developer and Trainer at Model Mind AI) sits down with CEO Loren Horsager to explore one of the most exciting developments in AI: agents. This episode introduces listeners to the concept of AI agents—what they are, how they differ from traditional automation, and why they’re emerging as a transformative force in 2025.

If workflows are step-by-step recipes, AI agents are your sous chef. They adapt on the fly, remember your preferences, and might even complete the task before you ask. Sound too good to be true? Loren and Angela explain how it works—and why now is the perfect time to get started.

From Recipes to Sous Chefs

Angela opens with a simple metaphor: workflows are like recipes—reliable but rigid. AI agents, by contrast, operate more like sous chefs who adapt based on context. They know your style, understand your kitchen, and anticipate needs. This analogy sets the stage for understanding why agentic systems are different from traditional automation.

What Makes a True AI Agent?

Loren breaks down the components that define a true AI agent:
- A core language model
- Memory capabilities to retrieve context
- Task-specific knowledge or goals
- A communication layer to interact with users or other agents

The real magic happens when multiple agents work together—each one specialized, with its own role and memory. These multi-agent systems hold immense potential, but also raise new design and communication challenges.

Human-in-the-Loop and Voice Interaction

One of the most exciting shifts is how we communicate with agents. Loren shares that teams are moving beyond chat interfaces to voice and collaborative environments like Microsoft Teams. Voice agents offer a more natural interface, especially for non-technical users. Angela sees this as a major accessibility advantage—and a key to broader adoption.

Agents for Deep Research

Loren shares how he uses AI agents to run deep research overnight. By seeding a question at the end of the day, he returns in the morning to insightful, structured output—saving time and generating new thinking. Angela compares this to moving beyond surface-level search to strategic partnership. It’s an early glimpse into how AI might soon help us think, write, and plan.

Where to Start with Agents

Getting started doesn’t require coding skills. Loren recommends exploring platforms like CrewAI or experimenting with agents that support research, operations, or internal tasks. Angela emphasizes that these tools are here now—and waiting isn’t an option. The best path forward is to start small, experiment, and learn in cycles.

Final Thoughts

AI agents represent the next step in business automation—from reactive tools to proactive, context-aware collaborators. They’re not a silver bullet, but they are a serious opportunity. As Loren notes, the teams that begin testing now will be the ones best positioned to scale later.

Ready to explore your own AI agent opportunities? Try the AI Readiness Assessment at modelmind.ai or contact the Model Mind team for hands-on support.

And as always, don’t forget to subscribe to *The Conversation* for more insights across AI readiness, training, and innovation.

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#7 AI Strategic Leadership

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Episode #5 AI Workflows and Automations