AI, Economics, and Why Iteration Beats Impatience

How Effective Collaboration Works

We recently experimented with a newly announced, cutting-edge AI. We gave it a long and detailed prompt, asking it to create a dashboard to aggregate information from several websites (via RSS feeds).

We submitted the prompt, but the result was a message saying 'Internal error occurred'. We tried again after refining the prompt slightly, but got the same outcome.

The request, ambitious and detailed, simply overwhelmed the system when asked to deliver everything at once. Despite its power, the AI hit a wall, unable to process and generate such a complex, interconnected output in one go.

While our first reaction might have been disappointment, this 'failed' experiment didn't reveal some fundamental weakness in AI. Instead, it perfectly validated our core philosophy.

AI-assisted creation, especially for complex tasks, is more like a conversation—an iterative process—than impatient waving of a magic wand. Expecting any AI, however advanced, to read your mind and generate a complex, flawless application from a single prompt is a recipe for frustration. That's not how effective collaboration works, whether it's with a human teammate or an AI assistant.

While chasing 'one-shot miracles' can be fun, we focus on reliable methods. We don't promise unrealistic shortcuts. Instead, we equip beginners with the practical, realistic, and ultimately more powerful process of collaborating with AI to bring ideas to life, step-by-step.

This is also where we bump into something quite profound. The situation echoes a basic economic axiom: human wants are unlimited. As AI becomes more powerful, our demands will continue to outpace its capabilities. We'll devise increasingly complex requests, and AI systems will struggle handling them, no matter how powerful they grow.