AI Agents do your work for free. And anyone can make them. So I wanted to write a how-to guide.
But then I got carried away. The guide’s now massive (and growing), because agents touch nearly every part of AI implementation.
So here are six key lessons so far:
💼 Working with chatbots is like managing an intern on their first day. They don’t have the tools, information or business understanding to get work done - so we hesitate to give them any.
🔨 Agents give LLMs the tools, workflows, and data they need to fully own tasks, not just assist.
🧑💻 Technical ability is no longer a barrier to automation. I’m a no-code kinda guy but I’ve had no problems with some-code tools like N8N as ChatGPT offers the worlds best tech support.
✏️ Start simple. A well written prompt + data is a great start and often enough. Complex systems hide issues, so only add advanced workflows when absolutely necessary.
🔁 The most successful agents so far (coding and customer support), both have straightforward validation steps (compiling successfully or customer satisfied). Checking work and feeding back suggestions are even more important in agent systems as LLMs prioritising helping to the point of making things up.
🤖 The potential for agents goes beyond task automation. LLMs may have human-like intelligence, but they’re also tireless machines. Why not research that subject? Reply to those emails? Delegate that task?
Still reading? Love long documents about robots doing your job?
OK, here’s the 👉👉 full guide 👈👈