Then sitting there refreshing the page, waiting for responses.

Twenty-four hours later: zero responses.

The tool itself? Actually pretty decent. Did exactly what it promised, worked perfectly fine for you.

But here's what happened: people clicked the link, saw a blank text box with no instructions, tried random inputs that gave weird responses, and left.

Those people? They're never coming back. Doesn't matter how much you improve the tool now - you've lost them at hello.

Let’s get started:

You had me at hello

The Five Second Rule

No, not the one about dropped food (though if you're eating while building AI tools, I admire your multitasking skills!).

I'm talking about the reality of first impressions. It’s like meeting someone in real life. You have scant moments to make a positive impression. Fail to do so and they’ll not be interested - or, worse - actively dislike you.

Harsh? Yes. True? I’m afraid so.

Ditto with your tool. When someone lands on your AI tool, you've got about five seconds before they decide if it's worth their time.

Don’t muck it up!

Think about using a new app. If you open it and have no clue what to do next, how long before you close it? Exactly.

Your tool needs to pass what I call the "Five Second Test":

• What does this thing do?

• How do I use it?

• Will it actually help me?

If users can't answer these in five seconds, they're gone. And they're probably not coming back. Why would they?

The Welcome Message

Your welcome message isn't just a greeting - it's your tool's handshake, elevator pitch, and user manual all rolled into one.

Here's what a good one needs:

1. Clear purpose ("This tool helps you...")

2. How to use it ("Just enter...")

3. Example inputs ("Try something like...")

4. What to expect ("You'll get...")

Let’s use a prompt to help you craft one:

You help create clear, engaging welcome messages for AI tools. Based on the tool details provided, generate:

1. Opening greeting that sets the tone
2. One clear sentence explaining the tool's purpose
3. Quick instruction on how to use it
4. 1-2 example inputs that showcase common use cases
5. Expected outputs for each example
6. Any important limitations or requirements

Tool Details:
[Describe your tool's purpose and functionality]

Provide both casual and professional versions of the message, explaining when each might be more appropriate.

You want this to be short and punchy.

Note: if the explanation is long and convoluted this may be because your tool isn’t focused single use like we discussed! Remember when we discussed not building an all-in-one tool and instead keeping it focused? Be mindful here.

We’re going to include your welcome message here if using LaunchLemonade:

Spend a good amount of time refining your welcome message. If people don’t make it past this message then all your subsequent work is wasted!

We’ll be diving more into refining, testing, collecting feedback and turning this into a proper “product” in the next Playbook.

Let’s take a moment to recap what we’ve covered though as it’s a lot!

Part 1: Stop Planning, Start Building We broke free from the preparation trap. Remember Sarah with her elaborate Notion board vs Mike who just started building? The key lesson: movement creates clarity. You learn more from doing than planning.

Part 2: Prepping Your Base Prompt We started in ChatGPT, crafting that first basic prompt. No fancy tools, no complex systems - just getting that core input/output working. One thing in, one thing out. The foundation of everything that followed.

Part 3: Moving to LaunchLemonade Time to give our prompt a proper home. We could have built everything from scratch, but why? Platforms exist to handle the complex bits while we focus on what matters - making something useful. We chose Launch Lemonade for its simplicity and direct access to multiple AI models.

Part 4: Adding Context This is where our tools started getting smart. We learned about the Goldilocks principle of context - not too much, not too little. Just like hiring someone on Upwork, we figured out exactly what information our AI needs to do its job well.

Part 5: Getting Ready to Share Finally, we made our tools user-friendly by nailing the welcome message. Fail here and we’ve lost them!

In the next Playbook we're diving into proper testing and refinement. We'll look at:

• Error handling

• Gathering meaningful feedback

• Making iterative improvements

• Scaling what works

• Packaging into a product

But for now, you've got everything you need to build your first AI tool. Remember - it doesn't need to be perfect. It just needs to exist! That’s the big takeaway.

The real learning starts when you put something out there and see how people use it. So go build something. Make it simple, make it clear, make it helpful. The rest comes later.

Keep Prompting,

Kyle