❌ Stop getting mediocre results with AI [Workshop]

Hey there.

By now, most professionals have at least experimented with AI. They've tried ChatGPT for research, tested Claude for writing emails, or asked Gemini or Grok to help with analysis.

But far too many end up with mediocre results that make them think AI isn’t good enough to increase their productivity.

They get completely different responses when they ask the same question twice, get told “facts” that turn out to be completely wrong, receive vague, generic responses when they need specific, actionable insights or end up with walls of text that don't really apply to their situation.

What most of them don’t realize is that these issues aren't caused by AI limitations… they're the result of communication problems. And, fortunately, there are specific ways to tackle every single one.

Here are the techniques we’re exploring this week inside The Rundown AI University:

Technique #1 — Applying important professional context

When AI responses feel generic it’s because the model doesn't understand your specific professional environment, constraints, or standards. Without properly formatted context, AI treats a CEO's strategic question the same as a student's homework help.

The first technique worth learning teaches AI to adopt the perspective, expertise level, and professional standards you actually need. Instead of getting textbook responses, you receive insights that account for your industry's realities, regulatory requirements, and business guidelines.

What this technique adds:

• Industry-specific vocabulary and concepts that match your field

• Appropriate depth and sophistication for your role level

• Responses that consider real-world constraints and limitations

• Professional formatting and tone that matches workplace standards

• Context-aware recommendations that fit your organizational culture

This method will instantly improve your strategic planning, client communications, technical documentation, competitive analysis, stakeholder presentations, and any task where generic advice falls short of professional requirements.

Technique #2 — Guiding predictable step-by-step “thinking”

AI interactions can seem like magic tricks when you get an answer but have no idea how the model arrived at it. This lack of transparency makes it impossible to trust complex outputs or know that all bases have been covered.

The second approach we’re exploring guides AI through the same logical steps a human expert would follow to break down complex problems into manageable, predictable steps. Instead of randomly responding to a request, AI repeats an established process to catch more potential errors and produce more reliable conclusions.

What this technique adds:

• Transparent reasoning that you can follow and verify

• Higher accuracy on complex, multi-step problems

• Ability to identify and correct errors in the logic chain

• More reliable outputs for high-stakes decisions

• Structured problem-solving that builds on previous steps

This technique is an instant upgrade for financial analysis, research synthesis, strategic decision-making, technical troubleshooting, process optimization, and any complex problem that requires logical progression and verification.

Technique #3 — Shaping the output to match a specific standard

One of the biggest frustrations with AI is the constant back-and-forth trying to get the right format, tone, or level of detail. Most people end up revising their requests multiple times, often unsure how to articulate what’s missing.

The third method our members are focusing on helps AI models understand exactly what excellent output looks before they respond to your requests. It's like giving AI a brief training session for each new type of task to dramatically improve consistency and reduce revision cycles.

What this technique adds:

• Consistent quality and format across similar requests

• Elimination of time-wasting revision cycles

• Precise control over tone, structure, and detail level

• Reliable replication of successful patterns

• Immediate alignment with your specific standards and preferences

This approach is especially useful for content creation, report writing, email templates, data analysis formats, presentation structures, and any recurring task where consistency and quality control are essential.

Professionals who are armed with these techniques will consistently receive more reliable results from the leading tools.

Even if you’re already using AI to be more productive at work, understanding how to improve your prompts is an untapped superpower.

And that’s what we’re equipping you with in this week’s workshop…

Join Dr. Alvaro Cintas at 4 PM ET, this Friday, to learn:

• How to structure prompts for clarity, control, and creativity

• The techniques and approaches that unlock significantly better results

• How to tailor your prompts across use cases like writing, coding, and research

By the end of this workshop, you'll have practical strategies to get AI models to do exactly what you want.

If you’ve struggled to get AI tools to consistently meet your expectations, these techniques will be invaluable in your career. 

Boost your productivity by mastering prompting techniques that give you more reliable AI responses with a free 14-day trial at The Rundown AI University.

See you in class, 

The Rundown Team

P.S. The professionals who can most effectively communicate with AI models will be the ones leapfrogging past their peers and defining how AI is used in their organizations. Grab this no-risk, no-brainer opportunity to learn prompting techniques that you can implement by Monday morning by starting a 14-day trial here.