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.
AI tools that automate marketing often produce low-quality, spammy content. The key to success is using AI to handle tedious tasks, which frees you up to apply your unique taste and expertise across a higher volume of content. AI should amplify your quality, not replace it.
AI tools cannot create value from nothing. To succeed, you must first establish a "human center of mass"—a core piece of high-quality, human-driven content or a valuable product. Only then can AI be effectively used as an amplifier to create clips, newsletters, and other derivatives.
As AI agents handle more complex, time-consuming tasks, productive users will run multiple agent sessions in parallel. This mirrors delegating to a coworker and forces a shift towards a multitasking workflow that requires managing several concurrent AI-driven activities.
Don't get bogged down with complex skill creation templates. The most effective method is to engage in a feedback loop: have an AI agent perform a task, correct its output until it's perfect, then simply instruct the agent to turn that successful interaction into a new, reusable skill.
The next evolution of creating AI skills is moving beyond text instructions. Tools like OpenAI Codex's "Record and Replay" allow you to perform a task on your computer while the AI agent observes your screen, mouse clicks, and keyboard inputs, then automatically converts that workflow into a repeatable skill.
Today's AI agents like Codex primarily operate as single-player tools on your desktop. The next wave involves multiplayer agents that live in collaborative spaces like Slack. These team-based agents can be accessed by anyone, share knowledge, and automate group workflows, creating new challenges in permissions and shared memory.