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.
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.
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.
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.