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The Calum Johnson ShowAI Runs My Entire Business: EASY Way To Use AI Agents In Your Work, Content & Life (Step by Step!)
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At a glance
WHAT IT’S REALLY ABOUT
Playbooks turn AI agents into reliable, reusable operators for work
- Rachel Woods explains how she uses AI agents that follow written “playbooks” to complete work reliably, including a case where her system handled more than eight hours of tasks while she was sick.
- She distinguishes between agents (more autonomous AI) and playbooks (step-by-step instructions), arguing that playbooks are what make agentic work trustworthy and repeatable.
- She demonstrates a project-planning playbook in Claude that asks clarifying questions, proposes options, drafts tasks and timelines, identifies which tasks AI can execute, and can push the plan into a task tool.
- She attributes a major jump in practicality to saved instruction “skills,” which let her store playbooks inside AI tools for quick loading and reuse instead of relying on heavier automation setups.
- She outlines a four-part playbook template—trigger, inputs, steps, outputs—and emphasizes improving the system by editing the playbook itself rather than repeatedly correcting one-off chats.
IDEAS WORTH REMEMBERING
5 ideasPlaybooks let agents run real work for hours with minimal supervision.
She described being extremely sick, typing one trigger word to start her daily routine playbook, and having agents handle tasks like inbox management, rescheduling, proposal updates, reporting, and funnel building because the work was pre-organized into playbooks.
Reliability comes from fixing the playbook, not arguing with the chat.
She framed playbooks as reusable step-by-step instructions that make AI output consistent and trustworthy, so you don’t have to repeatedly correct the model in chat; when something’s wrong, you update the playbook so future runs improve.
The better first question is ‘How do I build my first playbook?’ not ‘How do I build my first agent?’
She argued that people often fixate on building an “agent,” but if the agent doesn’t follow a defined process, you can’t control quality; she noted that many tools already behave agentically, and the differentiator is the instructions you give them.
Saved ‘skills’ accelerated playbooking by making workflows easy to reuse.
She said a key recent shift was the ability to save instruction sets as “skills,” so an AI can load a playbook on demand without building slow, complex automation flows; this made it faster and easier to scale playbooks across work.
“Own the playbook, rent the tech” reduces tool-chasing and lock-in.
She emphasized writing playbooks as tool-independent documents so you can run the same process across different AI tools, reducing anxiety about constantly switching platforms.
WORDS WORTH SAVING
5 quotesMy AI did over eight hours of work without me having to be the one driving it.
— Rachel Woods
We have a philosophy, own the playbook, rent the tech.
— Rachel Woods
I haven't even slowed down recently to really realize just how our business could not exist without playbooks.
— Rachel Woods
I have not met a process or type of work that I couldn't playbook.
— Rachel Woods
It's not really about AI. It's really about operations.
— Rachel Woods
SPEAKERS
Rachel Woods
guestAI operations and automation expert focused on building agent/playbook systems for business workflows.
Calum Johnson
hostHost of The Calum Johnson Show, interviewing guests about AI, business, and productivity.
High quality AI-generated summary created from speaker-labeled transcript.
