Prompt Playbook: Building your first AI App PART 3

There's a certain temptation when building AI tools to do everything yourself.

This is my go-to reaction: “I can do this myself!!”

After all, if you know how to code, you could build a custom application, hook it up to the OpenAI API, handle the authentication, set up a database, create a nice interface...

All perfectly doable if you're technically minded! In fact it’s getting easier day by day with new AI coding tools like Cursor and Windsurf.

But here's the thing - it's a massive time sink. Setting up infrastructure, debugging API calls, handling rate limits, building user interfaces. Before you know it, you're three weeks in and haven't even started on the actual useful bit of your tool.

And that's assuming you know how to code! If you read the above and it was gobblygook then even more reason to avoid! If you don't know about this sort of stuff, you're looking at months of additional learning before you can even start.

But we’re AI entrepreneurs. We want to build and launch ASAP.

Let’s get started

Foundational Prompt

Wrapping it up

Yesterday we looked at crafting the perfect prompt. Today we're giving that prompt a home - somewhere users can actually interact with it.

It’s no good just having our prompt in ChatGPT. We want to able to sell access to our tool - which means just giving them a prompt isn’t going to hack it. We’ll need a way for people to sign up, pay, access your tool etc. etc.

This adds layers of complexity beyond the simple input, process, output we’ve been discussing so far. We need a vehicle around the work we’ve done so far.

Sure, you could build everything yourself. It's totally doable. But here's the thing - every hour spent setting up infrastructure is an hour you're not spending on what matters: solving your users' problems.

Enter LaunchLemonade

Remember Cien from the last part? She helped me build a box finder in a couple of hours.

Turns out she can build more than a simple box finder! She’s the co-founder of LaunchLemonade, a no-code platform that lets you build AI tools without worrying about the technical stuff.

Think of it as a layer of abstraction - you focus on what your tool does, they handle how it does it.

Think about driving a car. You don't need to understand how the engine works to drive - you just need to know about the steering wheel, pedals, and gear stick. The complex stuff is hidden away, letting you focus on getting where you need to go.

Hell, reading a book about all the inner workings of a car would get you no closer to being able to drive to the shops.

That's exactly what a platform like LaunchLemonade does. Instead of worrying about APIs, authentication, and databases (the engine), you just focus on what matters: your prompt and how users will interact with it (the steering wheel and pedals).

Building AI tools can work the same way. Let the platform handle the complex bits while you focus on making something useful.

Key features that matter for us

• Access to 16+ AI models (ChatGPT, Claude, Gemini, LLaMa etc.)

• File and image handling built-in

• Ability for users to register and pay for your tool

• Simple publishing process

But most importantly - you can go from prompt to working tool in minutes, not weeks.

I’ll tag Cien in to introduce and give an intro herself

Here’s a sign up link too to get access. Not an affiliate, just a fan of the tool: https://launchlemonade.app/

Choosing your model

We’ll get into the details of exactly how to set up your instructions, database and other building blocks of your app in the next Part.

For now though let’s cover the issue of what model to use!

When using a tool like LaunchLemonade you have access to more than just ChatGPT. There may be a better model for your particular task. Choosing the right model is a super important first step because they’ll perform differently.

Ultimately I recommend testing your prompts and the tool with lots of different models to see what comes out with the best result. But because there are so many we can at least try to narrow it down first.

Let’s use a prompt to suggest a model

You are an AI model selection specialist. Based on the following parameters, recommend the best AI model for this specific use case.

Project Parameters:
Purpose: [Describe what your tool will do]
Input: [What information are users providing?]
Process: [What transformation/analysis needs doing?]
Output: [What results are users expecting?]

Please provide:
1. Primary model recommendation with reasoning
2. Alternative options with reasoning
3. Key considerations for this use case
4. Any potential limitations to be aware of

For example, with yesterday's box finder

• Purpose: Recommend storage boxes based on space dimensions

• Input: User's available space measurements

• Process: Compare against product database

• Output: Three best-fitting box recommendations

The prompt suggested GPT-3.5 since it's

• Cost-effective for simple comparisons

• Fast enough for real-time recommendations

• More than capable of handling basic dimension matching

• Perfect for this kind of straightforward matching task

Key here is that the recommendation is not the objectively best model. Because there’s no need! More advanced models cost more to deploy and are slower. So we generally want to use the model that is “good enough” and no more.

FYI Cost per usage is less of a problem when using LaunchLemonade because it’s flat pricing. When using direct API we pay for each query (a further complication).

Getting Started Today

Head over to LaunchLemonade and create your account. I’m not an affiliate and this isn’t sponsored. Feel free to use another tool if you prefer! But I’ll be sticking to LaunchLemonade for these tutorials.

Don't worry about building anything yet - just get familiar with the interface. Click around. Break things (in testing, obviously!).

Keep Prompting,

Kyle