How I Built a $5,000 Mobile App Using DeepSeek AI and ChatGPT for Beginners

How I Mastered Building a Mobile App Using DeepSeek AI and ChatGPT for Profit

Crafting a mobile app using tools like DeepSeek AI and ChatGPT opened my eyes to a world of possibilities, blending creativity with technology to generate profit through platforms like Google AdMob. I stood as a curious observer, watching someone skillfully navigate the digital landscape to bring a simple idea to life. The journey began with a clear goal: to create a functional app with minimal cost and maximum efficiency. It was a process that required setting up accounts, generating code, and testing functionality, all while aiming for a seamless user experience. What unfolded was a masterclass in leveraging AI tools for app development, a skill anyone can learn with the right guidance. I took mental notes, eager to share the steps that transformed a basic concept into a money-making reality. The experience highlighted the power of modern tools in democratizing app creation. Let’s dive into the detailed process I witnessed, breaking it down into manageable lessons.

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Setting Up Accounts with DeepSeek AI and ChatGPT

The first step I observed was the foundational task of setting up accounts on DeepSeek AI and ChatGPT, a process as straightforward as signing up for a newsletter but pivotal for the journey ahead. I watched as the individual navigated to the DeepSeek website, where a clean interface greeted them with a sign-up button prominently displayed on the homepage. They clicked it, revealing a form asking for basic details like email and password, which they filled out with ease, confirming their account via a quick email verification link. The same steps were mirrored on the ChatGPT platform, where the OpenAI login page offered a similar user-friendly experience, guiding them through account creation in mere minutes. It struck me how accessible these tools are, requiring no advanced technical knowledge—just a willingness to engage with AI. Once both accounts were active, a dashboard appeared on each platform, brimming with options like chat interfaces and API access, setting the stage for the app-building process. This initial setup felt like unlocking a toolbox, each platform ready to contribute unique strengths to the project. It was a reminder that starting small with the right tools can lead to big outcomes.

Crafting the Perfect Prompt for a Calculator App

Next, I watched as the individual prepared to interact with the AI tools by crafting a precise prompt, a task that seemed to blend creativity with technical clarity. They typed into the DeepSeek AI interface: “Create a simple calculator app with arithmetic operations, a display to show results, and mobile responsiveness, providing separate HTML, CSS, and JavaScript code.” The prompt was clear, breaking down exactly what was needed, which I noted as a critical lesson in communicating with AI—specificity yields better results. The screen displayed their words in a neat text box, with a “Submit” button glowing invitingly at the bottom. Upon clicking it, the AI began processing, a small loading icon spinning as if to signal the magic happening behind the scenes. I realized this step was about more than just asking for code; it was about defining the app’s purpose and structure upfront. The individual leaned back, confident in their request, knowing the AI would soon deliver usable snippets. It dawned on me how empowering this process is—turning a simple idea into actionable code with just a few well-chosen words. This moment underscored the importance of clarity when working with AI tools.

Observing AI in Action with DeepSeek and ChatGPT

As the AI tools kicked into gear, I observed the fascinating interplay between DeepSeek AI and ChatGPT, each working to generate the requested code for the calculator app. The screen flickered slightly as DeepSeek produced the first set of results, presenting neatly organized sections labeled “HTML,” “CSS,” and “JavaScript.” The individual scrolled through the output, their eyes scanning lines of code that defined a basic calculator layout with buttons for numbers and operations. ChatGPT followed suit, offering a slightly different styling approach in its CSS, which added a sleek gradient to the buttons, making them pop visually. I noted how both tools complemented each other, providing options to mix and match elements for a better design. The process felt like watching two expert coders collaborate in real-time, each bringing a unique perspective to the table. The individual copied the code snippets into a text editor, ensuring they were saved separately for easy integration later. This step highlighted the efficiency of AI in app development—hours of manual coding condensed into minutes of generation and review.

Integrating Code into a Development Environment

With the code generated, I watched the individual move to integrate it into a development environment, a practical step that brought the app closer to reality. They opened a code editor—Visual Studio Code, with its dark theme casting a professional glow on the screen—and created three new files: index.html, styles.css, and script.js. The HTML code from DeepSeek was pasted first, forming the skeleton of the calculator with a grid of buttons and a display area at the top. Next came the CSS from ChatGPT, which they adjusted slightly, tweaking the button padding to ensure a snug fit on smaller screens. The JavaScript followed, a concise script that handled arithmetic operations like addition and subtraction with event listeners tied to each button. I observed their methodical approach, ensuring each file linked correctly in the HTML header, a small but crucial detail. They opened a local server to preview the app in a browser, revealing a functional calculator that responded to clicks with satisfying precision. This integration phase taught me the importance of patience and organization when translating AI-generated code into a working product.

Testing and Verifying the App’s Functionality

The final step I witnessed was the testing phase, where the individual ensured the app worked as intended, a critical part of the development process. They clicked through the calculator’s buttons on their laptop screen, inputting simple equations like “5 + 3” and watching the display update to “8” in real-time. Each operation—addition, subtraction, multiplication, division—was tested methodically, with the individual noting any lag or errors in a small notebook beside them. I saw them encounter a minor bug where the “clear” button didn’t reset the display fully, prompting a quick return to the JavaScript file to adjust the reset function. After a few tweaks, the app ran smoothly, even on a mobile browser they tested via their phone, the buttons resizing perfectly thanks to the responsive CSS. This testing phase was a lesson in diligence, showing how even AI-generated code needs human oversight to ensure quality. They also explored Google AdMob integration, setting up an account to monetize the app, a step that promised future revenue. Watching this process unfold reinforced the idea that building an app is as much about refinement as it is about creation.