Improve AI Results
Diagnose generic or inaccurate AI outputs by improving context, scope, examples, audience details, and success criteria.
Build practical AI systems for marketing that improve output quality with better context, reusable project libraries, reliable workflows, and focused prototypes.
Diagnose generic or inaccurate AI outputs by improving context, scope, examples, audience details, and success criteria.
Build reusable context libraries and projects that preserve company, customer, campaign, and process knowledge for repeated marketing work.
Structure AI work sessions that ask clarifying questions, develop ideas progressively, and avoid overloaded conversations.
Apply AI to research, synthesis, critique, drafting, and customer insight work where it can reliably improve marketing speed and quality.
Design narrow AI workflows for lead enrichment, proposal support, competitor monitoring, CRM cleanup, and other repeatable operations.
Prototype dashboards, calculators, lead magnets, and internal tool mockups that make marketing decisions and software ideas easier to evaluate.
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.