Episode #5 AI Workflows and Automations
Episode 5 Recap: “AI Workflows—Turning Everyday Friction Into Efficiency”**
In Episode 5 of *The Conversation*, Angela Schultz and Loren Horsager explore the nuts and bolts of AI workflows and automations. This isn’t about futuristic robots or coding wizardry—it’s about solving real workplace friction with smarter systems anyone can build. From hiring emails to marketing reports, Loren shows how automation is the clearest path to real business efficiency. Read on to learn the difference between workflows and agents, how to validate what you build, and why business users—not just IT—should be in the driver’s seat.
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Episode 5 – Workflows & Automations: Turning Friction Into Freedom
In Episode 5 of *The Conversation*, Angela Schultz (Curriculum Developer and Trainer at Model Mind AI) sits down with CEO Loren Horsager to explore a topic that brings real energy to AI adoption: building smart, sustainable workflows and automations. This episode isn't just about tools—it's about how to think like a builder, solve problems from the ground up, and remove friction from work in ways that feel personal and powerful.
Why AI Workflows Matter
Model Mind’s AI Readiness Framework includes workflows and automations for a reason. While other elements—like governance or training—lay the foundation, it’s workflows where things get exciting. Loren explains that automations are where organizations start to see real returns. When teams can automate recurring tasks, structure repeatable steps, and personalize systems without heavy IT lift, that’s where the magic happens.
Friction as a Starting Point
Angela kicks off a fun segment called 'Workflow Wins'—real workplace challenges that AI can solve with simple workflows. Loren responds with practical examples: automating interview scheduling emails, consolidating campaign data from multiple marketing platforms, and updating project boards automatically. The core idea? If something’s repetitive and predictable, AI can handle it—and teams don’t have to wait for IT to build the solution.
Tools of the Trade
From Trello and Microsoft Teams to Make.com and N8N, Loren outlines several tools that enable business users—not just developers—to create powerful automations. These platforms are increasingly intuitive, with natural language guidance, visual builders, and embedded AI support. The best part? Many are free or open source, making them accessible even to small teams or solo entrepreneurs.
Who’s Building These Workflows?
Historically, workflow design was reserved for technical teams. Today, business users can—and should—take the lead. Angela shares how she used AI to understand complex workflows and how empowering it felt to be part of the solution. Loren emphasizes that pairing business context with technical know-how is the key to successful implementation. Sometimes, it’s one person wearing both hats. More often, it’s a small team working collaboratively.
From Rigid to Responsive
Old workflows were brittle. If one exception broke the process, the whole system failed. Now, AI enables flexibility. Loren explains how today’s workflows can detect outliers, trigger human-in-the-loop approvals, or even rewrite themselves as new needs emerge. The ability to test, iterate, and adapt in real-time makes modern automations dramatically more robust.
Design with the End in Mind
Angela and Loren emphasize starting with the output. What’s the desired result? Then work backward. In one case, Loren shares how a client designed a lease agreement analyzer by breaking down each task the human used to do—and replicating those in smaller AI-powered steps. Testing, validation, and even retry loops were baked in from the start to ensure quality and reliability.
The Role of Validation
It’s not enough for an AI workflow to work once. Loren stresses the importance of testing with 20 or more real-world cases to ensure consistent outputs. Angela adds that AI can help identify the edge cases and guide your validation plan. While full automation is the goal, partial automation can still save massive time—and teams can expand it over time as confidence grows.
Agents vs. Workflows
What’s the difference between a workflow and an agent? Loren breaks it down: workflows follow a structured, step-by-step path. Agents have tools, rules, and autonomy to decide how to act. They’re powerful—but riskier. Angela and Loren agree that for many business use cases, starting with structured workflows makes the most sense.
Real Business Impact
From marketing content generation to invoice processing, Loren shares examples where automated workflows have cut weeks off delivery cycles, removed the need for manual updates, and enabled more strategic focus. One highlight: a system that writes, scores, and refines marketing content based on AI-generated quality assessments. Hundreds of steps. Fully automated.
Prompt of the Week
Angela wraps with a prompt that mimics a workflow. It helps users sort their Monday morning emails into four categories, generate replies, and prioritize what matters. It’s a micro-example of the bigger message: workflows don’t need to be complex to be transformational.
Final Thoughts
AI workflows and automations aren’t just shortcuts—they’re upgrades. They enable scalability, clarity, and creativity across teams. And as Angela says, when you start with friction and build with clarity, AI becomes a teammate, not just a tool.