While AI can run tasks autonomously, creatives must stay "in the loop." Avoid simply accepting AI output; instead, provide constant feedback to shape the result until it feels authentically yours. This prevents generic, soulless work and ensures you remain proud of the final product.

To move beyond basic AI tasks, chain multiple skills together. A "skill chain" runs a sequence of specialized AI skills—like drafting, copywriting, and quality assurance—to produce a complex output with higher fidelity and less human intervention.

While AI can help draft "skills" (reusable prompts), research shows human-authored skills perform better. This highlights the value of domain expertise. Use AI as a starting point, but refine instructions with specific knowledge, templates, and context for optimal results.

Instead of asking an AI for a one-off task, identify recurring workflows and have the AI turn them into a "skill." This creates a reusable asset that dramatically improves efficiency and output quality over time, turning the user into a system builder.

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.

Expecting employees to author perfect, complex prompts from scratch leads to paralysis. A better method is letting them complete a task via iteration with the AI, then having the system automatically capture those adjustments as a reusable workflow or 'skill.'

Instead of perfecting a single prompt, treat AI interaction as a rapid, iterative cycle. View the first output as a draft. Like managing an employee, provide feedback and refine the result over several short cycles to achieve a superior outcome, which is more effective than front-loading all effort.

Instead of pre-designing a complex AI system, first achieve your desired output through a manual, iterative conversation. Then, instruct the AI to review the entire session and convert that successful workflow into a reusable "skill." This reverse-engineers a perfect system from a proven process.