❌ 7 reasons people DON'T join the University

(and what they do instead...)

March 24, 2025

Hey there.

Thanks for reading these emails each week.

We hope they're helping you make progress in your work, one way or another.

Of course, if you're reading these emails each week, that means you haven't started your free 14-day trial yet.

And we get it.

The Rundown AI University is not for everyone.

In this (slightly longer) email, we're being transparent about some of the legitimate concerns that keep many people stuck in the "interested, but not ready" phase.

And, we'll even share what different professionals are choosing to do instead 👀

Here are the most common reasons people DON'T join the University:

1. They don't think they have time to learn AI right now

With packed calendars, back-to-back meetings, and existing responsibilities that barely fit into a workday, the thought of adding "learn a new technology" to the to-do list feels impossible. Many professionals say they're already stretched thin and can't imagine where they'd find extra hours for learning something new, even though they know it's important.

What they do instead: They stick with their current workflows, promising themselves they'll make time "in a few months" when things calm down. While this approach ensures they maintain their current levels of productivity, they often spend too much time on tasks that could be automated — creating a cycle where they always feel too busy to learn how to save time in their work.

What they don't realize: Most video lessons in the University take just 5-10 minutes and are designed to deliver immediate time savings that compound daily. The focus is specifically on high-impact workflows that create more time rather than consuming it. After watching workshops like "Building AI Agents that automate tasks" or following guides like "Create your own AI-powered email assistant," many members discover that the initial time investment is repaid within days, not weeks or months.

2. They believe they can figure out AI on their own by experimenting

Many professionals pride themselves on being self-sufficient learners. They've mastered other tools and technologies by diving in and experimenting and, understandably, they assume AI will be no different. The amount of free resources online that promise incredible results reinforce the belief that they can piece together what they need through random tutorials and articles.

What they do instead: They invest time in independent learning — reading blog posts, following YouTube videos, experimenting with different prompts… and trusting overnight influencers. This approach can result in solid outcomes and valuable personal insights, but often involves a lot of trial and error, reinventing workflows others have already optimized, and navigating conflicting advice. Many get occasional wins but also face frustrating inconsistencies and dead ends, with no clear path forward.

What they don't realize: Self-directed learning becomes significantly more efficient with structured guidance. Inside the University, workshops like "How to select the best LLM for your use case" and guides like "How to prompt o1 models better" compress weeks of experimentation into days by combining non-obvious techniques in ways that would often take hundreds of hours to discover.

3. They're already using ChatGPT and don't see what more there is to learn

Having successfully asked ChatGPT some questions and received helpful answers, quite a few professionals believe they know everything AI has to offer. The basic interface seems straightforward, and they're getting some value, which can make additional learning seem unnecessary.

What they do instead: They use AI as a smart assistant for simple tasks like drafting emails, generating ideas, or answering straightforward questions. This approach delivers genuine value and often improves on their previous workflows. However, they typically only use the most obvious capabilities — treating advanced AI tools like a slightly better search engine or writing assistant, rather than unlocking their full potential.

What they don't realize: Most people only use about 10-20% of AI’s actual capability. Workshops like "Mastering Claude 3.7 Sonnet: Advanced AI for Reasoning & Coding" and guides on "Build your next SaaS using AI deep research" reveal a world beyond simple prompts. They end up missing out on automated workflows, connected tools, and custom systems that handle complex projects with minimal oversight.

4. They fear AI education could be too technical for them

Many professionals without coding backgrounds assume learning AI requires technical expertise they don't have. They worry they'll be quickly out of their depth or that the content won't be applicable to their everyday work.

What they do instead: They stick to basic, surface-level AI interactions that don't require technical knowledge. This cautious approach helps them avoid feeling overwhelmed and lets them gradually build confidence with simpler tasks. They continue to consume entry-level information, which often lacks enough depth to create any meaningful impact .

What they don't realize: The University was specifically built for non-technical professionals. Workshops like "AI for Coding: From 0 to 100" and guides like "Customize Claude responses to match your writing style" focus on practical implementation by allowing members to see it, copy it, and customize it without any existing experience. Rather than theoretical explanations, our lessons show exactly what to click and type at every step.

5. They have concerns about using AI in their specific role or industry

Often professionals see examples of AI in content creation or programming but struggle to connect those use cases to their particular job. They work in specialized fields with unique challenges and aren't convinced AI can meaningfully address their specific needs.

What they do instead: They consider AI to be "relevant for other roles but not mine" and focus on traditional tools and methods that are specific to their industry. This method makes sense because they don’t want to waste time on general-purpose AI. However, they often miss opportunities to apply AI to unique industry challenges simply because the benefits aren't immediately obvious.

What they don't realize: Courses and workshops that cover a wide range of industries are the most popular feature of the University. Sessions like "Lindy AI for Instant Pre-call Meeting Briefs" and guides like "Find perfect prospects with AI" help our members apply AI in completely different contexts. Even highly specialized professionals regularly discover applications they hadn't considered possible, in fields that seemed too niche at first.

6. They're unsure if the investment will pay off

With so many subscription services competing for their budget, professionals are rightfully cautious about adding another expense. They wonder whether the knowledge gained will translate to tangible value.

What they do instead: They restrict themselves to limited versions of AI tools and carefully allocate their learning budget to what they consider essential. Yes, this approach helps them avoid unnecessary expenses.. However, it often leads to knowledge gaps and missed opportunities that would deliver far greater returns than the initial investment.

What they don't realize: The typical return on investment comes through time savings, new capabilities, and avoiding expensive mistakes. Many members are able to turn what they learn into larger salaries and invoices, too. Tutorials like "Turn your long videos into bite-sized clips" and "Transform meeting recordings into actions and insights" automate tasks that previously took hours. And for many professionals, saving just 1-2 hours each week more than justifies the investment.

7. They're waiting for AI to be more sophisticated before they fully dive in

With new AI announcements every week day, many professionals feel the need to wait for the “right” time. They know today's technology is a stepping stone to something better and that something more advanced is just around the corner. As a result, they worry that whatever they learn might quickly become outdated each time the technology evolves.

What they do instead: They keep an eye on AI news and developments, occasionally trying new features when they're released. This "wait and see" approach feels like a good idea as the industry evolves so rapidly but, in the meantime, that delay can keep them lagging behind and unable to truly benefit from AI right now.

What they don't realize: Best practices for effective AI implementation remain the same, even as the technology improves. Even though workshops like "Using Google Gemini 2.0 to Edit Images & Create Content With Simple Natural Language" are released within days (or hours) of major AI releases, the focus remains on transferable skills rather than tool-specific tricks. Guides such as "How to build your own free AI Operator" build a foundation that makes adapting to each advancement significantly easier, ensuring that the knowledge gained remains valuable regardless of which new features or models emerge in the coming months.

What most of our members discover

Despite their initial hesitations, professionals who join the University find that AI implementation is often simpler than they expected. Many of them tell us that they wish they’d joined sooner. 

But that doesn’t mean their hesitations weren’t valid.

And that’s why The Rundown AI University includes a 14-day trial — to remove the risk and give anyone the opportunity to see if it’s a good fit for their career. 

You can explore workshops like "Building & Monetizing Mobile Apps" or guides like "Turn research papers into interactive learning sessions," and still decide it's not the right fit. 

No hard feelings.

For most professionals, the realization that AI implementation doesn't have to be overwhelming, technical, or time-consuming changes everything. What seemed like "one more thing to learn" becomes "the thing that makes everything else easier."

See you inside,

Rowan & The Rundown Team

P.S. If you've been feeling uncertain about whether you can really leverage AI right now, workshops like "Using Personalized Video to Scale Outreach" and guides like "Turn your articles into video podcasts" will help you find clarity. Get immediate access to our complete library of practical AI use cases with a 14-day trial here.