The Startup Ideas Podcast
The best businesses are built at the intersection of emerging technology, community, and real human needs.
Within 18 months, there will be a stark divide between businesses getting high-quality AI outputs through structured prompting and those stuck with 'AI slop' from basic usage.
The Reasoning
AI models are becoming more sophisticated and responsive to advanced prompting techniques, but most users aren't learning these methods. This creates an expanding quality gap between basic and advanced usage that compounds over time as AI becomes more central to business operations.
What Needs to Be True
- AI models continue improving their response to structured prompting
- Most users remain unaware of advanced techniques
- Business competition increases pressure for AI ROI
- Quality differences become measurable in business outcomes
Counterargument
AI models might become so good that prompting technique becomes less important, or AI companies might integrate better prompting assistance directly into their interfaces, reducing the skill gap.
What Would Change This View
If AI companies successfully build intuitive interfaces that guide users to better prompting automatically, or if AI models become significantly more forgiving of poor prompts while maintaining quality.
Implications for Builders
Opportunity to build AI prompting education businesses
Competitive advantage for companies that invest in AI communication training early
Demand for AI productivity consultants and trainers
Market for tools that provide prompting templates and guidance
Example Application
“A consulting firm that masters structured prompting delivers client reports in half the time with twice the quality, while competitors struggle with time-consuming AI output revisions.”