Generative AI is basically the Guitar Hero of the creative world

Anyone who played Guitar Hero knows the feeling—you're hitting all the colored notes in perfect time, the crowd is cheering, and you feel like a rock god, but you aren't actually playing a guitar. You're just triggering pre-recorded sounds by pressing plastic buttons. This is the perfect analogy for how most people use generative AI for "creativity" today. We are essentially playing a high-tech version of a rhythm game where the "notes" are our prompts and the "song" is the output from a latent space.

The core issue is the gap between execution and intent. In traditional art, the struggle—the shaky line in a sketch or the wrong chord in a song—is where the actual creativity happens. It's the human error and the subsequent correction that give a piece of work its soul. With LLMs or image generators, we've outsourced the execution entirely. When you use a complex prompt to generate a "cinematic shot of a futuristic city," you aren't composing a scene; you're selecting a preset.

To move past this "plastic guitar" phase, we need a more sophisticated AI workflow. Instead of treating the AI as a vending machine where you put in a prompt and get a finished product, we should be looking at it as a collaborative agent. This means moving toward a more iterative, hands-on guide approach to creation.

Shifting from Generation to Curation

If you want to actually create something original, you have to stop relying on one-shot prompts. The real work now lies in the curation and the "surgical" editing of AI output.

• The Prompting Phase: Stop trying to get the "perfect" result in one go. Use the AI to generate 50 divergent ideas, then kill 48 of them.
• The Refinement Phase: Take the remaining two and manually break them. Change a specific detail, introduce a contradiction, or force the AI to rewrite a section from a completely opposing perspective.
• The Integration Phase: Merge the AI's structural efficiency with your own specific, lived-experience details that a model simply cannot hallucinate because it hasn't lived a life.

The danger is that we get so addicted to the dopamine hit of a "perfect" AI-generated image or paragraph that we forget how to actually develop a taste. Taste is developed through failure and iteration. If the AI removes the failure, it risks stagnating the taste of the creator.

We are currently in a transition period. We're moving from the "wow" phase—where we're impressed that the AI can draw a hand with five fingers—to the utility phase. The people who will actually thrive aren't the ones who can write the most elaborate prompts, but those who can treat the AI as a raw material. The goal shouldn't be to let the AI be the artist, but to use it as the most advanced brush ever invented. When you stop trying to "play the game" and start actually shaping the output, that's when the real creativity kicks in.