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What if the reason your AI automations keep falling apart isn’t the AI, it’s the way you’re defining the work?
Most businesses are still using AI as a smarter search engine or an occasional assistant. But if you want AI to reliably take work off your plate, you need something much more structured.
In this episode of Leveraging AI, Isar Meitis sits down with AI entrepreneur and former Facebook AI team member Rachel Woods to break down the concept of AI playbooks — repeatable, detailed processes that allow AI to execute business tasks consistently and reliably.
Rachel shares the framework she uses to turn everyday business processes into AI-powered systems. The idea is surprisingly simple: define the trigger, inputs, steps, and expected output. Then break complex workflows into smaller pieces that AI can execute extremely well.
In this session, you'll discover:
Why most AI automations fail when you give AI too much freedom
How to turn existing business processes into AI playbooks
The four components every AI playbook needs
Why breaking complex workflows into smaller tasks dramatically improves AI performance
How Rachel uses more than 100 playbooks to help run a 10-person company
How AI can manage email triage, content creation, project planning, and other operational workflows
Why you should “own the playbook and rent the tech”
How to build reusable AI processes that aren't dependent on ChatGPT, Claude, or any specific platform
Why your first AI playbook probably shouldn't be built by AI
How individual playbooks can eventually work together like an entire AI team
Rachel also walks through real examples, including her LinkedIn content workflow and a project-planning system that helped her team dramatically increase the number of projects they can execute.
If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!
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