Lead Practical AI Adoption
Set AI priorities that emphasize safe ROI, team trust, practical experimentation, and repeatable business value.
Build practical AI adoption habits that help leaders improve productivity, guide teams safely, design low-risk workflows, and create clear policies for responsible use.
Set AI priorities that emphasize safe ROI, team trust, practical experimentation, and repeatable business value.
Give AI the company, role, market, goals, constraints, examples, and data it needs to produce useful work.
Create reusable AI projects for leadership tasks such as one-on-one preparation, performance reviews, sales enablement, and RFP support.
Break complex processes into smaller AI tasks, workflow steps, and narrow agent decisions that are easier to test and improve.
Define clear AI usage expectations, reduce shadow AI risk, and evaluate higher-risk workflows with real examples and accuracy checks.
Document repeatable processes as SOPs that support delegation, automation planning, and future agent readiness.
1 part · 6 chapters

AI Educator @ The Rundown University
Nate is a SaaS founder and Fractional CMO who helps product-driven businesses build marketing systems that actually work — without the fluff. He's spent years helping founders and operators cut through marketing complexity and put the right things on autopilot.
At Rundown University, Nate brings that same hands-on, no-jargon approach to AI education. His workshops and courses focus on practical automation and AI workflows you can deploy the same day — no engineering background required. If you've ever wanted to use AI to get your time back, Nate shows you exactly how.