Stop overcomplicating it. Here are the rules that actually matter when you're starting with AI automation.
I see a lot of people trying to build complex AI agent systems before they understand the basics. Here's the advice I wish someone gave me when I started.
Never automate a process you haven't done manually at least 5 times.
Why? If you can't write down the logic step-by-step on paper, you can't build it in any tool. You need to understand the edge cases first.
A common mistake: someone tries to automate their entire client onboarding without ever documenting what the steps actually are. They automate the happy path and everything else breaks.
People spend weeks debating n8n vs Make vs Zapier vs custom code.
The truth: For 90% of business automations, any of these tools will work. Pick one and master it. Switching costs are real and time spent debating is time not spent building.
The most valuable automations aren't impressive — they're boring:
These save hours every week. Nobody writes a blog post about them. But they're the foundation.
Your automation WILL fail. APIs go down. Data formats change. Rate limits hit.
Build error handling from day one:
If you can't measure the impact, you can't justify the investment.
Before you automate anything, measure:
After automation, measure the same things. The delta is your ROI.
If your automation has more than 15 nodes/steps, it's probably doing too much. Break it into smaller, independent workflows that communicate through webhooks or queues.
Why? Debugging a 40-node workflow is a nightmare. Debugging four 10-node workflows is manageable.
Automation is a skill, not a tool. Master the fundamentals — data flow, error handling, API basics — and every tool becomes easier. Don't chase complexity. Chase reliability.