Don't just save good prompts; codify entire successful back-and-forth conversations into reusable "skills" within AI platforms like Claude. This automates complex, multi-step tasks like content repurposing with a single command, saving significant time.

Instead of trying to automate a whole job like "running ads," break it down into its smallest component tasks (e.g., "write copy," "set budgets"). Use AI as a tutor to help automate each tiny task individually, making the overall process manageable and effective.

Don't view AI as a tool to replace roles. Its power is in collapsing multi-day processes—like creating and QA-ing an advertorial—into minutes. The most valuable skill marketers can develop is learning to construct custom workflows by connecting various AI models via APIs to amplify their own output and speed.

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.

Go beyond single-use skills by chaining them together. For instance, a daily 'morning brief' skill can be designed to automatically trigger a 'podcast guest research' skill whenever a podcast is detected on your calendar. This creates complex, multi-layered automations that run without manual intervention.

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.

To scale your use of AI agents, move beyond single-use builds. Identify recurring capabilities and package them as reusable 'skills.' This modular approach makes your work transportable, allowing you to easily apply successful processes across different projects and agents, which compounds your efficiency over time.

Frame tasks as a chain of "and then" actions an infinitely staffed team would perform. For example, a customer query in Slack is answered, "and then" AI turns it into a help article, "and then" it becomes SEO content. AI makes these previously cost-prohibitive workflows achievable.

To maximize AI's impact, don't just find isolated use cases for content or demand gen teams. Instead, map a core process like a campaign workflow and apply AI to augment each stage, from strategy and creation to localization and measurement. AI is workflow-native, not function-native.