The No BS Guide to Building Your First AI App – No Coding Needed
A Step-by-Step Guide to build your own app with zero coding skills
Building an AI-powered app might seem intimidating, but with AI coding tools like Bolt, you can create functional applications without deep programming knowledge. This tutorial will walk you through building a custom storybook app for toddlers where parents can generate personalized stories using their child’s name, pet’s name, and AI-generated illustrations.
By the end of this guide, you’ll understand:
How to set up a project in Bolt
How to integrate OpenAI’s DALL·E API for AI-generated images
How to debug and optimize AI-generated code
Best practices for structuring AI-generated projects
This step-by-step guide is designed for beginners looking to explore AI-powered app development without writing complex code.
AI coding tools have fascinated me for a while. As a Principal PM, I don’t code daily, but I understand logic and system design. When I came across Bolt, an AI-powered coding tool, I wanted to test whether I could build a working app from scratch—without writing a single line of code.
For this experiment, I decided to build a custom storybook app for toddlers (ages 1-2). The goal was to let parents generate personalized stories with their child’s name, pet’s name, and AI-generated images.
This post will walk through:
How I built this app using Bolt
How I integrated OpenAI’s DALL·E API for AI-generated images
Common challenges & how to fix them
Tips to make AI-generated code work better
By the end, you should be able to replicate this process and build your own AI-powered app, even if you have no coding experience.
Step 1: Define What We Want to Build
The custom storybook app should:
Let parents enter their child’s name, pet’s name, and pet type.
Generate a simple, engaging story using these inputs.
Fetch a DALL·E-generated illustration that matches the story.
Display everything in a clean, responsive UI.
Since this was an MVP (Minimum Viable Product), I constrained the scope:
Only five pre-written stories (to prevent overcomplication).
Simple UI with text-based input (no need for fancy animations).
AI-generated images for each story (instead of manually adding them).
Step 2: Tools Used
To build this, I used:
1. Bolt – The AI Coding Assistant
🔗 Bolt is an AI-powered coding tool running on Claude Sonnet 3.5 that generates functional code based on natural language instructions. Instead of manually writing code, you just describe what you want, and Bolt generates it. To build this app, we need to purchase a $20 monthly subscription, and I think it’s worth it. (I am not affiliated to Bolt)
2. OpenAI’s DALL·E API
🔗 OpenAI provides an image generation API that allows us to create AI-powered illustrations based on text descriptions. This was used to generate custom images for each story. I had purchased about $10 worth of credits.
Step 3: Setting Up the Project in Bolt
1. Create a New Project
Go to Bolt.new and create a new project.
Select React as the framework or specify in the prompt that you want a web app.
2. Give an Initial Prompt to Bolt
Since AI-generated code can get messy, I started with a very clear, constrained prompt to ensure Bolt doesn’t overcomplicate things.
Prompt:
"Create a simple responsive web app that displays short children's stories. The user should enter the child’s name, pet’s name, and pet type in a form. The story should be generated using these inputs. There should be five predefined stories, and each story should have a matching AI-generated image."
📌 Tip: Keep your AI prompts clear and structured. Here's an example:
❌ Vague Prompt: "Create a storybook app."
✅ Better Prompt: "Create a simple responsive web app that allows users to input a child's name, pet’s name, and pet type. The app should generate a predefined short story using these inputs and display a matching AI-generated image.". Bolt tends to over-engineer solutions if you give vague instructions.
I am asking only for 5 stories in the beginning so that it is simple. If I don’t specify, there is a chance that Bolt may overcomplicate.
Step 4: Bolt Generates the Base App
After running the prompt, Bolt generated a basic web app with:
A form for child’s name, pet name, and pet type
Predefined five short stories
A simple page navigation structure
🚨 What went wrong?
Bolt generated functional code but with several limitations.
Static images were hardcoded instead of being dynamically generated.
The form design was too basic and lacked interactivity.
There was no error handling or validation for user inputs.
Navigation between stories wasn't smooth, making the UX clunky.
Fixing the UI
I asked Bolt to improve the form:
Prompt:
"Make the form more interactive. Add icons for pet types. Ensure text boxes are visually clear as input fields."
✔ Now, the form looked better. But still, the images weren’t dynamic.
Step 5: Integrating DALL·E for AI-Generated Images
Since the hardcoded images didn’t match the stories, I had to integrate OpenAI’s DALL·E API.
1. Creating an OpenAI API Key and .env File
Before using the OpenAI API, you need to generate an API key to authenticate requests securely. Storing API keys directly in your code is a security risk, so it's best practice to use a .env (environment) file to keep sensitive information separate.
Steps to Generate and Store an OpenAI API Key Securely
Generate an API Key:
Go to OpenAI’s API dashboard.
Log in or create an account.
Navigate to the API Keys section and generate a new secret key.
Ask Bolt to Create a .env File:
Instead of manually adding the key to your code, store it securely in a .env file.
Use the following prompt to instruct Bolt:
Prompt:
"Create a .env file to store the OpenAI API key. Update the code to fetch the key from the .env file instead of hardcoding it."
Manually Add the API Key:
Once Bolt generates the .env file, open it and paste your API key in the following format:
OPENAI_API_KEY=your_api_key_hereEnsure your application reads the API key from the .env file instead of storing it in the main codebase.
By following this method, you enhance security and prevent exposing API keys in public repositories. This is a best practice when working with external APIs like OpenAI’s DALL·E.
Before using the OpenAI API, I needed to create an API key:
Go to OpenAI’s API dashboard
Create an account or log in
Navigate to the API Keys section and generate a new secret key
Once I had the key, I asked Bolt to create a .env file to securely store it:
Prompt:
"Create a .env file to store the OpenAI API key. Update the code to fetch the key from the .env file instead of hardcoding it."
After Bolt generated the file, I manually copied the API key into it to ensure security.
2. Generating Images Dynamically
I gave Bolt a new prompt:
Prompt:
"For each story, fetch an AI-generated image from OpenAI’s DALL·E API. The image should include the child, the pet, and a scene from the story. The API key should be stored in the .env file."
Bolt created the necessary API call to OpenAI, but there were some issues:
🚨 It didn’t generate new images for each story change.
🚨 There was a delay in fetching images, making the UI feel slow.
Since the hardcoded images didn’t match the stories, I had to integrate OpenAI’s DALL·E API.
Step 6: Debugging and Optimizing the App
1. Fixing the Image Issue – Ask AI to Explain Before Fixing
Before making any changes, always ask Bolt to explain the issue first. This ensures you understand the logic behind its decisions before modifying the code.
Prompt:
"Before making any code changes, explain why the image is not changing for each story. What part of the logic is causing this issue?"
✔ Bolt analyzed the issue and explained that the app was reusing the same image across all stories because it wasn’t fetching a new one when navigating between them.
By confirming the logic first, we ensured that any fixes wouldn’t introduce unnecessary complexity. Once satisfied with the explanation, we applied the fix.
Before making any changes, I first asked Bolt to explain the issue to ensure we understood the root cause. This is an important step because AI-generated code can sometimes overcomplicate solutions if we start fixing things without fully diagnosing the problem.
Fix:
"Ensure each story fetches a fresh image when navigating to a new story. Debug the logic if needed before making code changes."
✔ This helped, and Bolt correctly updated images for each story.
Bolt kept using the same image for all stories.
Fix:
"Ensure each story fetches a fresh image when navigating to a new story. Debug the logic if needed before making code changes."
✔ This helped, and Bolt correctly updated images for each story.
2. Reducing Latency in Image Loading
To fix the delay in fetching images, I added a loading animation:
Prompt:
"Add a loading animation when generating the AI image to improve the user experience."
✔ Now, the app didn’t feel unresponsive while images loaded.
3. Ensuring Character Consistency Across Stories
Each story’s image looked different (the kid and pet had no visual continuity).
Fix:
"Ensure the same child and pet character style is maintained across all stories."
✔ Now, the experience felt seamless.
Final Thoughts: AI Can Help You Build Apps, But we need to polish
This experiment showed me that AI can generate 70% of the code, but the last 30% (debugging, optimizing, refining) still needs human intervention.
Would I recommend this approach? Absolutely—for MVPs, quick hacks, or learning projects. For production-level apps, you’ll still need human oversight.
Key Takeaways & Next Steps
✅ AI tools can speed up development, but debugging and optimizations are still necessary.
✅ Structured prompts help AI generate cleaner and more functional code.
✅ Testing and iteration are essential—AI-generated code isn't always perfect.
✅ Bolt is great for MVPs, but production apps require human oversight.
If you enjoyed this tutorial and want to explore more AI-powered product development, follow my Substack for more in-depth insights! 🚀