OpenClaw 72 Hours: The Pitfalls Documentation Won't Tell You

Preface

I haven't slept much these past three days.

Not because OpenClaw is hard to use, quite the opposite—it's too good. It's so good that I kept thinking "let me try one more feature," and then I fell into various unexpected pitfalls.

As an indie developer, I've seen too many AI tools that "look beautiful." OpenClaw is different. It is the only Agent framework I am currently willing to invest time in deeply debugging and actually running in a production environment.

But honestly, the official documentation is written too "idealistically."

It's like those travel guides that only tell you how beautiful the attractions are, but won't warn you which restroom is the dirtiest or which road is the easiest to get lost on. So I decided to write this "pitfall guide" to record the pits I stepped into over these 72 hours.

Are you ready?

1. Why OpenClaw?

First, let's talk about the good parts.

1. Start Chatting in Two Minutes

I've tried LangChain and AutoGPT, and the configuration time is measured in "hours." OpenClaw is different; it really is two minutes.

Not an exaggeration, literally two minutes:

Download the project
Fill in a few API Keys
Run the startup command
Start chatting

For indie developers who need to quickly validate ideas, time is money. One hour less configuration means one more hour to think about product logic.

And it is compatible with so many models and skills. Want to try Claude? Change a Key. Want to try Gemini? Change a Key again. This flexibility saves so much trouble during the selection phase.

2. It Really "Understands" What It Needs to Do

This is the part that surprised me the most.

Most Agent frameworks need you to teach them hand in hand: use this skill for this task, call that API for that scenario. OpenClaw doesn't need that.

You just need to let it self-check once, then tell it your requirements, and it can activate 80% of the functionality.

Even more amazingly, it will:

Detect if it crashed and restart automatically
Detect missing functionality and actively add it
Detect simple requirements and implement them directly

This autonomy is particularly suitable for those tasks that don't require deep thinking but are tedious and repetitive.

But Watch Its Pace

OpenClaw prefers "fast in, fast out" tasks.

If a task takes 10 minutes to complete, it might not wait. If it finds no status return for 2 seconds, it will think it failed, and then retry or just give up.

It's like an impatient assistant—suitable for handling a large number of small tasks, not suitable for complex problems requiring "long thought."

What you need to do is break big tasks into small steps and let it complete them one by one, rather than throwing it a whole task that needs to run for a long time.

3. It Can Modify Its Own Code

This ability sounds a bit sci-fi, but it really works.

When you find a function doesn't meet expectations, you can let it review the code, find the problem, and modify the code itself. And it won't fall into an infinite loop; the stability is unexpected.

For indie developers without dedicated team support, this "self-repair" capability is a lifesaver.

Sounds Perfect? Wait

If OpenClaw were really that perfect, I wouldn't need to write this article.

The truth is, its advantages and disadvantages are equally obvious. And many pitfalls, you simply can't discover without actually running it for 72 hours.

Next, I'm going to talk about the four big pits, each of which made me break down at least once.