Learn the framework for directing AI agents — at your own pace.
The same framework taught in the live cohort — how to set up an AI system properly, prompt it well, connect it to your tools, automate a real process, and know what stays human — in eleven chapters you work through at your own pace.
We teach it hands-on in Claude, since right now it's the fastest way in — but the underlying skills transfer to any agentic AI system you end up using.
Who this guide is for
AI agents are already doing execution work across every field. Someone has to set the goals, audit the outputs, and own the results — this guide teaches you to be that person, in whatever field you're in.
AI agents are already generating content, running campaigns, and qualifying leads. This guide teaches you to direct that work instead of getting buried by it.
AI can draft it. You still have to own it. This guide covers what agents can and can't be trusted with, and how to build the oversight systems your firm depends on.
Agents are already handling AP/AR, categorization, and reporting. This guide teaches you to audit, direct, and quality-control that work.
Operations already runs on the structured, process-driven thinking that directs AI agents well. This guide turns that instinct into a repeatable skill set.
Scheduling, patient communication, documentation — agents are already handling pieces of this. This guide is for the person who oversees how it's done.
You don't need to be convinced AI is changing your field. You're here because you want a framework, a vocabulary, and a clear path — not more hype.
You want to build AI systems from scratch — this isn't a coding course. It's for the professional who directs agents, not the engineer who wires them up. If that's you, start at docs.anthropic.com. If you want to be the person in your organization who knows how to run what gets built, keep reading.
This guide is built hands-on in Claude because it's currently the most accessible way to actually learn this — not because the framework only works there. The mental model, the prompting structure, the connector pattern, the automation logic — all of it applies the same way in ChatGPT, Gemini, or whatever your organization already runs. You're learning the architecture. Claude is just where we teach it.
Eleven chapters, no filler
Set Up Your AI Foundation
Thirty minutes of setup — a system prompt, your first project, your prompt library — that changes how everything after this works, no matter which AI you're running it on.
Prompt Engineering That Actually Works
One structure (Role → Context → Task → Constraints → Format), five real prompts, and the habit that fixes most bad outputs.
Connect Your AI to Your Tools
Giving it hands: email, drive, chat — the connector pattern, whichever platform you're on.
The Four Components + Your First Live Connector
The mental model that ties it together, then your first connector that lets your AI actually act, not just read.
Build Your First Automation
Everything so far, wired into one real working system — manual first, automated second.
Where AI Shows Up In Your Workday
Browser, documents, live outputs, and multi-step work — four contexts, and when to reach for each.
From Idea to Live Website, No Code
Using Claude Code as the example — how a plain-language request becomes something live on the internet.
Train It Once: Build a Skill
Reusable instructions so you stop re-explaining the job every time.
Why Agents Fail (and How to Fix It)
A fast, tool-agnostic diagnostic for when something goes wrong.
Your Practice Path
A self-paced, week-by-week plan through everything above.
The Human in the Loop
What stays yours, no matter how good the tools get.
What you'll actually build
A working system prompt
A running prompt library
One live connector
One working automation-ready connector action
One real automation with a review step
One live no-code website edit
One custom Skill
A working failure-diagnostic habit
Someone who built the system
Christina Dills has spent 20+ years at the intersection of business operations and emerging technology — starting as a Microsoft intern and staying 13 years in its enterprise technology practice, then founding Smart Edge Technologies, an AI and emerging technology consultancy serving SMBs across Tampa Bay, South Florida, and Latin America since 2018.
She doesn't write about AI from the outside. She runs three AI-powered companies simultaneously on the exact infrastructure described in this guide — multi-agent systems, voice AI, automated CRM pipelines, and edge-deployed tools in active use with real clients. The Agent Operator framework came directly from those deployments: what worked, what failed, and what every non-technical professional needed to understand to stay in control.
Her work spans AI video analytics, blockchain, and IoT deployments for multinational companies, with consulting engagements across several Fortune 500 organizations on emerging technology strategy. She has been recognized by the Synapse Innovation Challenge (AI + IoT), the SBDC Award for Best Small Business across 10 Florida counties, and holds credentials from Harvard, Columbia, IBM, and Curtin University.
What people say
"I built a capability one-pager for my business and got real UI/UX feedback using Claude's Chrome extension — genuinely useful, immediate results. But the bigger shift was in how I think about Claude: I went from treating it like a single thinking partner to running it like three skilled employees, each with their own output to leverage."
"I've been deep in the AI space for about a year, using it to transform how I work and helping others see its real operational value. But this program cracked something open for me — it showed me how to take everything I'd been doing and actually wire it into the functioning of my business, not just as a tool I use, but as the engine that runs it. That's a completely different level."
"Before this program I was building with Claude in ways that worked, but self-taught, without a shared vocabulary for what I was doing. This cohort gave me a framework to name it — and confirmed that the most important design decision in AI adoption isn't which model you choose, it's how you structure the relationship between human judgment and the system."
Get the guide.
This guide gives you the same framework taught in the live cohort — the four components, the connector pattern, and a hands-on path to operational fluency — worked through at your own pace.
Questions? hello@agentoperator.co