Get your free personalized podcast brief

We scan new podcasts and send you the top 5 insights daily.

Instead of giving an AI agent one task at a time, combine a series of related steps into a single, comprehensive prompt. For example, when selling an item, ask the bot to research prices, write a description, post the listing, and automatically lower the price weekly.

Related Insights

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 a single complex prompt, break down marketing tasks into a series of smaller, single-purpose AI skills. For example, a content workflow can be chained: one skill for drafting, one for HTML generation, and another for platform-specific formatting. This modularity improves reliability and scalability.

The new frontier of interacting with AI agents involves creating systems that automate the prompting process. Users design "loops" that continuously prompt, check the output against a goal, and re-prompt the agent, turning their job into that of a system designer.

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.

Instead of immediately asking an AI to perform a complex task, first prompt it to create a functional spec or a sequential plan. Go back and forth to align on this plan before instructing it to execute, which significantly improves the final output's quality and relevance.

The power of AI agents lies in chaining simple tasks into complex workflows. For example, an agent can purchase an item online and then automatically update a corresponding inventory list in Notion. This creates a personal "operating system" that handles multi-step life administration tasks autonomously.

For large tasks like creating a business plan, act as a project conductor. First, prompt the AI for individual components like a table of contents or specific sections. Once all parts are generated, use a final prompt to synthesize them into a coherent whole.

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.

Instead of manually crafting complex "mega prompts" or training rules for AI assistants, ask the AI to generate them for you. You can have a dialogue with the AI to refine its suggestions, dramatically speeding up the process of creating sophisticated workflows.

Treat AI 'skills' as Standard Operating Procedures (SOPs) for your agent. By packaging a multi-step process, like creating a custom proposal, into a '.skill' file, you can simply invoke its name in the future. This lets the agent execute the entire workflow without needing repeated instructions.