Who this is for. This mini‑guide is written for professionals who juggle a 9‑to‑5 and/or a side hustle. You might be a marketer, analyst or designer who dabbles in freelance gigs after hours, or a creator building your own personal brand on evenings and weekends. You've tried ChatGPT but know there's more that AI can help you with. You're busy but curious about how AI agents could give you back time.

What you'll get. You'll learn what an "AI agent stack" is, why context matters more than clever prompts, and how to pick and deploy agents that do real work while you sleep. By the end, you'll have a small but powerful AI team wrapped around your workflows. So get curious and get excited!

I – Workflows, Automations & Agents

Before we go deeper, we need to align on the three layers of modern automation:

1. Workflows (the foundation). These are rule‑based, predictable sequences that run the same way every time. You map variables and conditions, and the system executes step‑by‑step. You can build a solid efficiency engine just by mastering this layer.
2. AI automations (the hybrid layer). Here you sprinkle in intelligence (for example, using AI to personalise an email or categorize a support ticket). The flow is still deterministic, but AI helps make small decisions. Most business use cases fall here.
3. AI agents (the top layer). Agents are systems that make decisions, reference memory, use tools and adjust based on context. They can feel like digital teammates — but they're non‑deterministic and easier to break if you don't know your workflow. I wouldn't jump here right away. It's good to start with the basics.

The key takeaway: Spend a week mapping your workflows and automating them deterministically. Only then do you layer on AI automations and, finally, agents for the work you really don't need to do yourself.

II – The Transition Curve

When I first started with agents, I was honestly a mess. I'd see demos on Twitter, get hyped, open the tool… and nothing would work. Things broke constantly. I'd set something up, think I'd nailed it, and then it would just fail in weird ways I couldn't debug.

But I kept going. I'd hop on to YouTube, ask people what I was doing wrong, watch someone else's setup, try again. Slowly, I started to get it. Not because agents suddenly got easier — they didn't — but because I learned how to work with them instead of expecting them to just "get it."

I'm in a much better place now. I actually enjoy working with agents. They're not like ChatGPT where you ask a question and get an answer. They need more from you: clearer instructions, better context, a bit of patience.

But once you figure that out, it's a completely different way of working.

You're not just prompting anymore. You're building a system that runs things for you.