AI 代理 vs 傳統自動化：差在哪、該怎麼選？

Both Can Be Automated, But Fundamentally Different

Traditional automation (such as early Zapier) and AI agents can both "automate tasks," but they operate in vastly different ways, and choosing the wrong one can lead to inefficient results.

Traditional Automation: Rule-Based

Traditional automation is based on fixed rules: "if A, then do B". It has clear trigger conditions, fixed steps, and predictable results. Its advantages are stability, reliability, and affordability, making it suitable for repetitive tasks with clear rules that don't require much judgment (e.g., "send a notification when a form is received").

AI Agents: Judgment and Adaptability

AI agents add "understanding and judgment": they can handle unforeseen situations, break down steps, and choose tools on their own. The advantages of AI agents are flexibility and the ability to handle ambiguous tasks (e.g., "research this topic and write a report"), but the drawbacks are that they are less predictable, more expensive, and require supervision.

How to Choose

• Clear rules, repetitive, and stable: use traditional automation (Make, Zapier).
• Ambiguous tasks, requiring judgment or creativity: use AI agents (Lindy, Manus, CrewAI).
• Combining both is the most practical approach: use automation for stable processes and embed AI in the judgment-required stages. Many tools (such as n8n, Relay.app) can do both.

Common Misconceptions

Don't use AI agents for everything — tasks that can be solved with fixed rules are better handled by traditional automation, which is more stable and cost-effective. AI agents are best used in situations where "rules can't be predefined".

Conclusion

It's not that "AI agents are always better," but rather "choose the right tool based on the task nature". Use automation for stable rules and agents for ambiguous judgments, and combine them for the best results. For further reading: How to Build Your Own AI Agent.