We scan new podcasts and send you the top 5 insights daily.
Mystical systems like the Tarot, Zodiac, and Greek pantheon are not just historical artifacts; they function as a 'color wheel' of human experience. This archetypal literacy can be used as a sophisticated programming language for AI, allowing creators to infuse outputs with specific, coherent human feelings and character by prompting with archetypes like 'Be the magician' or 'Be Mercury'.
A novel AI use case from the creative industry: actors can feed a character's traits into an LLM's context window. They then query the model to explore how the character might react in various situations, providing a tool for deeper performance preparation and script development.
When prompting, especially with voice, use emotional and ambitious language. Pushing the AI to make something "brilliantly serendipitous" can elicit more creative responses, particularly from advanced models. This human-like interaction can improve output quality.
The true power of AI for knowledge work is formulating unique prompts derived from obscure or cross-disciplinary knowledge. This allows users to extract novel ideas that standard queries miss, making deep, non-mainstream reading a key competitive advantage in the AI era.
To avoid generic LLM responses, a user "trains" her agents by providing them with an identity built on literature. By telling an agent it has read and finds specific books fascinating, its outputs become quirkier and more aligned with a desired persona.
Instead of relying on complex text prompts, use a curated mood board as a direct visual input. Generative models like Midjourney can interpret the aesthetic, color, and style from images more effectively than from descriptive words, acting as a powerful communication shortcut.
A strong brand archetype acts as a powerful 'behavioral constraint' for AI, guiding it beyond generic outputs. By prompting AI with specific brand traits derived from the archetype (e.g., 'be visionary' or 'be precise'), teams can generate on-brand copy that is 80% complete, requiring only human judgment for the final nuance.
Seemingly non-technical prompts like "let's step back and think really hard" or "make it simpler and dumber" are highly effective. They work by adding key concepts to the AI's input context, which forces the model to change its mindset and extrapolate from that new framing, leading to better outputs.
The tendency for AI models to "make things up," often criticized as hallucination, is functionally the same as creativity. This trait makes computers valuable partners for the first time in domains like art, brainstorming, and entertainment, which were previously inaccessible to hyper-literal machines.
If you find yourself using the same complex prompt repeatedly, codify it into a "skill." A skill is a simple markdown file with instructions that the AI can invoke on command. You can even ask the AI to help you build the skill itself, raising the ceiling of its output and making your workflow more efficient.
The most effective way to use AI in creative fields is not as an automaton to generate final products, but as a tireless, hyper-knowledgeable writing partner. The human provides taste and direction, guiding the AI through back-and-forth exchanges to refine ideas and overcome creative blocks.