Working With Agentic AI (Part 1): Lessons From Building My Own AI Agents

🍀 What Leaders Need to Know Before They Begin Most people talk about AI like it’s magic. I don’t. Recently, I’ve started building multiple agentic AI systems for my own projects, and the truth is simple: AI only becomes useful when you learn how to work with it — not just what it can do. Over the past few months, I’ve created and trained several autonomous agents to support real workflows—project management, content operations, and technical oversight. That experience has been eye-opening, especially in showing where teams struggle when AI meets real work. Over the next few Saturdays, I’ll break down the practical side of Agentic AI—not the hype, not the jargon, but the real-world lessons leaders need to make these systems productive, safe, and aligned. Today, let’s start with the basics.

What Agentic AI Actually Is (Plain English)

An agent is an AI system designed to carry out work with intent and structure, not just respond to prompts.

At its core, an agent can:

• Understand a goal or intent
• Break work into steps
• Use tools and systems
• Make decisions within defined boundaries
• Deliver outputs that feel like partner-level support

This is why agents feel fundamentally different from traditional AI tools.

A helpful way to think about the shift is moving from a calculator to a junior analyst.

The calculator waits for instructions. The analyst takes initiative within constraints.

What agents are not:

• Not chatbots
• Not autonomous decision-makers
• Not replacements for human judgment

And this is the critical point most leaders miss: Agents don’t remove the need for human judgment — they amplify it.

Without the right structure, they don’t just make mistakes. They produce the wrong outcomes faster.

2. Ground Truth Is Everything

No agent is smarter than the information it’s grounded in.

In my own system, I rely on a structured Ground Truth layer—a curated foundation that includes:

• Facts
• Rules
• SOPs
• Proprietary frameworks
• Constraints
• Ethics and guardrails

This is what allows an agent to act consistently and correctly.

Without Ground Truth:

• You get drift
• You get hallucinations
• You get outputs that look polished but are fundamentally wrong

Rule #1: Before you give an agent autonomy, give it clarity.

3. What Agents CAN Do (High-Level)

When structured correctly, agents can:

• Draft content
• Maintain SOPs
• Map workflows
• Track backlog items
• Analyze documents
• Generate insights
• Prepare operating cycles
• Perform quality checks

They are powerful assistants.

But agents are not:

• Decision-makers
• Strategists
• Replacements for people
• A license to cut teams too fast

The ethics matter.

A better approach: Use AI to upskill people, not replace them. That’s how you get trust, innovation, and durable capability.

4. A Simple Use Case (Every PM Will Recognize)

Picture a project manager running a complex initiative.

An AI agent can:

• Generate weekly status updates
• Summarize risks
• Propose mitigations
• Track SOP drift
• Prepare leadership talking points
• Break down user stories
• Draft acceptance criteria
• Maintain a version log

The PM still provides:

• Interpretation
• Prioritization
• Escalation judgment
• Human context

No one gets replaced. Everyone gets leveled up.

This is how Agentic AI should enter project environments.

5. If You’re a PM Starting With Agents: Start Here

• Be patient — agents improve through structure
• Start small — one workflow, one output
• Change often — iteration is the point
• Document everything — if it isn’t written, the agent can’t use it
• Don’t expect magic agents to amplify strengths, not gaps
• Keep a human in the loop — always

Human oversight isn’t a limitation. It’s the safeguard.

6. What’s Coming in This Series

Over the next few Saturdays, I’ll cover:

• How to structure Ground Truth for predictable results
• What agents should never be allowed to do
• Ethics and leadership responsibilities
• How I use AI operationally in my own work
• A readiness checklist for leaders
• Practical templates for PMs

My goal is simple: Help leaders work with AI safely, strategically, and effectively.

If you’re exploring AI in your organization, start with readiness.

That’s why I built the StAIR-Ready™ assessment—to help leaders understand whether their people, data, technology, governance, and strategy are actually ready for AI.

Start with your free baseline at: WhereDoIStartAI.com

AI succeeds when readiness succeeds. Everything else is execution.

#AgenticAI #AILeadership #AIForBusiness #ProjectManagement #DigitalTransformation #FutureOfWork #StAIRReady #WhereDoIStartAI

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