There's been a lot of buzz lately about AI agents, and I wanted to share some observations from the trenches that might help you navigate this space more effectively.
You've probably noticed the flood of tools being marketed as "AI agents." Here's the thing though - many of these are actually sophisticated workflow automations dressed up in new clothing. As someone who's been building automation systems for years, I think understanding this distinction is crucial for making smart investment decisions.
Let's Break It Down
What makes an AI agent truly "agentic"? Here are the key characteristics:
Independent planning and execution of tasks
Ability to adapt to unexpected situations
Skill generalization across different scenarios
In contrast, workflow automations (even sophisticated ones) operate within predefined boundaries using conditional logic. Both are valuable, but they serve different purposes.
A Simple Evaluation Framework
When you're looking at a new tool, ask yourself these three questions:
How much is predefined? The more hardcoded logic, the closer it is to traditional automation.
Can it handle surprises? True agents can navigate unexpected scenarios without breaking down.
How versatile is it? Agents should be able to tackle varied problems within their domain.
The Reality Check
Here's what I've learned from years in the growth community: workflow automation isn't new. We've been building powerful systems with tools like Zapier and Make for years. What's exciting now is how AI capabilities are enhancing these proven workflows.
Practical Recommendations
Start with solid automation foundations
Gradually integrate AI capabilities where they add clear value
Don't get caught up in the "agent" hype - focus on solving real problems
The Big Picture
The distinction between agents and automations isn't about better or worse - it's about choosing the right tool for your specific needs. When vendors pitch their "AI agents," keep these distinctions in mind and focus on what actually solves your problems.
Best
Vincent