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I Challenged Myself to Code a $10k App with AI. Here’s What Happened. **Part 1: The Challenge** - I'm a marketer whose been selling software for over a decade. I've commissioned and sold hundreds of apps, some small $xxx projects, others mega-Saas Sites with six figure dev budgets and patents. A very technical marketer. Or a very non-technical founder. Both are true. I set a $10k app goal - could AI code apps that as recently as 2022 I was paying real developers five figures for, or even apps I paid 10k for back in 2018? Let's see **Part 2: The AI Arsenal** - Never would have considered coding apps myself (if budget is low, try `low code` devs or get creative with your marketing). But in October 2024, we have Cursor, Claude Sonnet, and GPT-O (with LARGE model of GPT-O on the horizon). Oh, and plus I've been building AI agents and bots since GPT 4 dropped in March 2023. I believed it was possible to code simple 3-5 page SaaS apps with AI.. and I was right. Firstly, I coded my first chrome extensions - just by describing the app to GPT-4 (yes the OG version). But this was only the beginning. With the advent of Sonnet 3.5 and Cursor, I moved to more expensive browser-based apps, using FireBase and a dozen APIs. And yes, spoiler: I coded apps I previously paid $15k for. **Part 3: Some secrets: Choose a language. I pick React.js with vanilla CSS (I couldn't install Tailwind in VS Code and gave up, AI makes me impatient). Secondly, template and save everything. Every successful AI code is a lesson for you - and less GPUs to burn in your next session with Sonnet 3.5 (watch those limits!) Use a api.js and .env file that you can reuse. Speaking of APIs, start with OpenAI's models as you can do a lot with vision, text, Whisper and of course the GPT series. That api.js is gold. Thirdly, choose an LLM AI coding tool - or a few. I recommend writing a very detailed prompt and asking the big GPT-O model to architect a full spec, then drop that plan into Sonnet 3.5. Refine your prompt with each app you build. My initial prompt is on its tenth iteration and GPT-O thinks for well over a minute every time I drop it in. **Part 3: The Future** - I've so far built half a dozen tools, and might look for a React dev to get involved, to help develop some more templates for me (and review the LLM-generated template code I currently have for mistakes). I hear there are many of them and they are cheap? I have sold a few very simple apps, and netted low five figures (not much given my distribution reach, but I consider this as big an opportunity as AI Agents which is saying something, so I can sideline the short-term cash grabs while I dive fully into this). I already have a backend dev so may rope him in to help with backend security (what's a Git??). Oh and I'm going to automate deployment with GitHub and Netlify next. No idea what any of this means but GPT-O does. **Part 4: A Rich Man? A Dangerous Future** - Yes I hit my 10k goal, and am convinced I can turn this into an agent setup for 2025. Apps with a Telegram voice command anyone? Oh, and I'm looking at iOS apps next. My goal for before Christmas? An Apple Vision app that I built entirely with my AI Agent, straight from a voice-command. That said, am I entering terrain I know nothing about? Perhaps I have no business being in these waters. Perhaps, in 2025 and 2026.. with agents, AI code, voice-assistants and agent-to-agent interactions.. none of us are ready for what's coming next.

Article 1 - chatgpt-4o-latest

# I Challenged Myself to Code a $10k App with AI. Here’s What Happened.

### **Introduction**

Can a non-developer create a $10,000 app using only AI tools? Before you answer, let me rewind a bit. I've spent over a decade marketing and selling software, working on everything from small apps costing a few hundred dollars to large-scale SaaS platforms requiring six-figure development budgets. Some even had patents. Despite all that experience, I never touched the actual coding side. I was always the “technical marketer” who could talk shop, but not the person to write the code.

But with AI advancing at a breathtaking pace, I became curious. Could I, without any real coding skills, leverage today’s AI tools to build apps that used to cost tens of thousands of dollars back in 2018? Could these AIs become competent developers? Finding out became my personal challenge: build a $10k app using AI. Let me walk you through what happened.

## **The Challenge Begins**

I began the experiment with excitement but also skepticism. I couldn’t code. At least not in the traditional sense. My plan was to see if I could use AI to replace developers entirely—or at least reduce the cost drastically. I set a realistic (but hefty) $10,000 goal. Could the tools available in late 2024 really create apps that, just a few years ago, I’d have paid real developers multiple five figures to build?

The answer, surprisingly, is yes—but not without some bumps along the way. Let’s dive into the toolkit that made it possible.

## **The AI Arsenal**

Picture this: we’re in October 2024, and AI tools like **Cursor**, **Claude Sonnet 3.5**, and **GPT-O** are everywhere. These tools handle everything from text generation to coding. I’ve been tinkering with AI agents since OpenAI launched GPT-4 in 2023, but now? It's a different game entirely.

The first project I built? A simple Chrome extension. It was a tool I used to track marketing analytics, and I described the functionality to OpenAI’s GPT-4 (the original version). Boom! A basic app came out of a simple description in plain words. I didn’t need to fiddle with the code, learn a coding language, or hire anyone. This win gave me the confidence to try something harder.

As the tools evolved, I upgraded to platforms like **Claude Sonnet 3.5** and **Cursor**, which enabled me to build browser apps using Firebase and a lot of APIs. Honestly, I couldn't believe I was pulling this off without traditional developers. Some of the apps I coded would have cost me $15,000 to develop a few years ago—with real developers. But here I was, letting AI do the heavy lifting.

## **Secrets to Make AI Coding Work**

Okay, so if you’re reading this and thinking, “I’m tempted, but I don’t know where to start,” let me share a few secrets I uncovered:

### 1. **Choose a Language and Stick With It**
In my case, I went with **React.js** and vanilla CSS (simple styling). I tried using **Tailwind CSS**, but I couldn’t install it in **VS Code**. Messing around with settings made me impatient, so I gave up (thank you, AI, for making me lazy!). But remember, the key here is to stick with a simple tech stack. The fancier you get, the more likely you’ll have hiccups.

### 2. **Save EVERYTHING**
Whenever AI generates code, templatize it. Every successful piece of code becomes a reusable asset. Save these snippets so you’re not recreating the wheel each time. I recommend keeping common files, like `api.js` and `.env` (which store your API keys and environment settings), and reuse them across different projects. This way, the next time you jump into a new project, you’re saving time (and AI compute resources).

### 3. **Master Prompts and Models**
The magic of AI coding comes down to what you tell the AI. Learn to refine your prompts. Aim for clear, precise language. For example, I’d ask GPT-O (the advanced model) to draft a **full tech spec**. Once I had the spec, I’d dump it into **Sonnet 3.5**, which would then code out all the logic for my app. The more apps I built, the more I tweaked my prompts. I’m on my tenth version of the initial prompt, and it's a mini novel at this point.

### 4. **Leverage APIs**
Jump into OpenAI’s suite of APIs when possible. Sure, GPT’s models can handle text generation, but they also excel with **Whisper** (for speech), **DALL-E** (for images), and **Vision capabilities**. All of these features can turn a basic app into something bigger and more interactive. I reused my `api.js` file across multiple projects this way, keeping development streamlined.

## **Successes—and Some Challenges**

Let’s talk results. I built several tools, some of which I ended up selling. I even netted low five figures from a few simple apps. Don’t get too excited though—given my extensive marketing distribution network, these earnings were modest. Still, I could see massive potential.

At this point, I began looking at more complex projects. I considered bringing in a React developer to help clean up some of the AI-generated code, especially the templates. (Apparently, AI isn’t perfect and errors do slip through.) I even found that React developers are now cheaper since AIs have shaken up the industry a bit.

My next hurdle? Getting deployment figured out. The AI suggested automating things using **GitHub** and **Netlify** for deployment pipelines. While I might have no idea what a “Git” is quite yet, GPT-O sure does—and at this point, I trust it. Automating deployment will save me a ton of hands-on time in the future and, honestly, it's probably where the industry’s heading next.

## **What’s Next? The Future Looks A Little Crazy**

The next few years are going to get wild. As for my experiment, yes, I hit my $10k goal, and now I’m thinking about what’s possible in 2025. Can I create full apps through just voice commands to an AI agent? That’s pretty much where I’m aiming next. Imagine talking to a Telegram bot that lets you control your whole app with voice, or visualizing your project, and just having the AI build it into an iOS app.

By Christmas, I’m aiming to develop an **Apple Vision** app entirely by voice command using AI tools like **Claude Sonnet** and **GPT-O**. Whether I succeed or fail spectacularly, one thing is clear: we’re approaching a future where coding looks completely different. And trust me, none of us are ready for it.

## **Conclusion**

So, did I achieve my goal? Absolutely. I built multiple tools and apps that would have cost me $10k or more in the past, all with the help of AI. But beyond hitting that number, this experiment opened my eyes to a bigger shift in how tech will be built moving forward. AI is making it possible for non-developers like me to create apps, potentially leveling the entire coding field in ways we haven’t fully comprehended yet.

As we dive deeper into 2025 and beyond, it’s clear that things are only going to get stranger and more powerful. Whether you're a marketer like me or someone just curious about AI, now is the time to jump in.

Are you ready for what’s coming? Because I barely am—but that’s what makes it exciting.

Article 2 - O1 Mini

# I Challenged Myself to Code a $10k App with AI. Here’s What Happened.

## Introduction

Can a non-developer create a $10,000 app using only AI tools? Imagine being a marketer with over a decade in software sales, handling projects from small gigs to six-figure SaaS platforms with patents. Now, picture setting a bold goal: build a high-quality app without hiring expensive developers. With AI tools like Cursor, Claude Sonnet, and GPT-O at my disposal, I decided to take the plunge. Could AI replace the hefty costs of traditional app development? This essay dives into my journey, the tools I used, the challenges I faced, and the surprising results that followed.

## Embarking on the Journey

As a marketer, I had always relied on developers to bring software ideas to life. But in October 2024, AI tools had advanced enough to make me rethink this approach. I started with simple projects, using GPT-4 to create Chrome extensions by just describing what I wanted. To my surprise, the AI delivered working apps quickly and efficiently. This initial success fueled my confidence to take on more complex tasks.

## Diving into the AI Arsenal

The real game-changer was the combination of advanced AI tools available in 2024. Cursor, Claude Sonnet 3.5, and the upcoming GPT-O provided the capabilities I needed to build more sophisticated apps. These tools had evolved significantly since GPT-4's release in March 2023, offering better efficiency and more features. With these AI assistants, I felt empowered to handle projects that used to cost thousands.

## Selecting the Right Language and Tools

Choosing the right programming language was crucial. I opted for React.js with vanilla CSS because it was simple and straightforward. Installing Tailwind in VS Code was too time-consuming, and I wanted to keep the process smooth and quick. AI tools influenced my workflow, making me impatient for anything that slowed me down. This choice allowed me to keep moving forward without getting bogged down by technical hurdles.

## Unlocking Secrets to Efficient AI Coding

Efficiency was key. I started templating and saving every successful AI-generated code snippet. Each piece of code was a lesson learned, helping me reduce GPU usage for future sessions with Sonnet 3.5. Creating a `api.js` and `.env` file became standard practice, saving time and resources on each new project. By reusing these elements, I streamlined the development process and made it easier to scale up.

## Mastering AI Prompts and Models

Creating detailed prompts was essential for guiding the AI. I developed a process where I used GPT-O to architect full specifications before feeding them into Sonnet 3.5. My prompts evolved with each app I built, reaching the tenth iteration where GPT-O started taking over a minute to process each request. This refinement ensured that the AI understood my needs better each time, resulting in more accurate and efficient code generation.

## Leveraging APIs and Environment Files

APIs played a significant role in adding functionality to my apps. I focused on OpenAI's models, utilizing vision, text, Whisper, and the GPT series to create robust features. The `api.js` and `.env` files were reusable templates that made integrating these APIs easier across different projects. This approach not only saved time but also ensured consistency and reliability in my app development.

## Overcoming Technical Hurdles

Despite my non-technical background, AI tools helped me navigate complex technical landscapes. Installing Tailwind was a challenge I chose to skip, but AI-assisted me in handling backend security and deployment automation. Concepts like Git, which were once foreign to me, became manageable with AI guidance. This reliance on AI allowed me to focus on building functional apps without getting stuck on technical details.

## Achieving Milestones

With the help of AI, I built half a dozen tools, each costing around $10k to develop traditionally. Selling these simple apps brought in low five-figure earnings. While this might not seem like much given my distribution reach, it's a significant achievement. It proved that AI could replicate the work of high-cost developers, opening up new opportunities for non-technical individuals like me.

## Collaborating and Scaling Up

To expand further, I considered bringing in a React developer to help develop more templates and review AI-generated code for errors. The market showed that many developers were available and affordable, making collaboration feasible. With a backend developer already on board, I planned to enhance backend security and automate deployment using GitHub and Netlify. Though I didn’t fully understand these platforms, GPT-O was there to guide me.

## Automating Deployment

Automation was the next step. I aimed to streamline deployment using GitHub and Netlify, relying on AI to handle the complexities. This move would save time and reduce errors, ensuring that my apps could be launched smoothly. Despite my limited knowledge, the AI assistance made this possible, further demonstrating the power of AI in simplifying app development.

## Future Ambitions and Innovations

Looking ahead, my goal was ambitious: build an Apple Vision app entirely through AI agents and voice commands by Christmas. I also envisioned integrating Telegram voice commands and exploring agent-to-agent interactions by 2025. These ideas pushed the boundaries of what AI could achieve, setting the stage for even more innovative projects in the near future.

## Reflecting on the Broader Implications

Achieving the $10k goal made me question whether venturing deeper into AI-driven development was wise. The rapid advancements in AI posed both opportunities and risks. As AI continues to evolve, the industry might not be fully prepared for the disruptions it could bring. This reflection made me ponder the future and the role AI would play in shaping it.

## Conclusion

Reaching the $10k app development goal using AI was a transformative experience. It showed that non-technical individuals could create high-quality apps without hefty developer costs. This paradigm shift empowers more people to enter the tech space, breaking down traditional barriers. As I look to the future, I’m excited about turning this process into a more advanced agent setup, exploring voice-commanded app creation, and navigating the uncharted waters of AI innovation. I encourage others to embrace AI tools and explore the limitless possibilities they offer. The rapid advancements in AI mean that adapting is no longer optional but essential. Are you ready for what’s coming next?

Article 3 - O1 Preview

# I Challenged Myself to Code a $10k App with AI. Here’s What Happened.

**Can a non-developer create a $10,000 app using only AI tools?**

I'm a marketer who's been selling software for over a decade. I've commissioned and sold hundreds of apps—some small projects costing a few hundred dollars, others massive SaaS platforms with six-figure development budgets and patents. I'm a very technical marketer. Or maybe a very non-technical founder. Both are true.

In October 2024, I set a challenge for myself: Could AI help me code apps that I used to pay real developers $10,000 or more to build? Could I, someone without traditional coding skills, create a five-figure app using only AI tools?

With the advancements in AI—tools like Cursor, Claude Sonnet, and GPT-O—I decided to find out. Since GPT-4 was released in March 2023, I've been building AI agents and bots. But coding full apps? That was new territory.

Here's what happened.

---

### Embarking on the Journey

I was both excited and skeptical. Tackling app development without traditional coding skills seemed daunting. But I began anyway. I started small. Using GPT-4—the original version—I coded my first Chrome extensions just by describing the app to it. It felt like magic.

### Diving into the AI Arsenal

That was just the beginning. With the advent of Sonnet 3.5 and Cursor, I moved on to more complex browser-based apps. I started using Firebase and a dozen APIs. These AI tools had evolved, offering more capabilities and efficiency. I was now coding apps I previously paid $15,000 to develop.

### Selecting the Right Language and Tools

I chose React.js with vanilla CSS. Why? Because it was straightforward, and I could get started immediately. I tried installing Tailwind in VS Code but gave up—AI has made me impatient. I wanted quick results, and React.js offered that.

### Unlocking Secrets to Efficient AI Coding

I learned to template and save every successful piece of AI-generated code. Every time the AI produced something that worked, I saved it. This way, I reduced GPU usage and optimized future AI sessions with Sonnet 3.5. I created a personal library of code snippets that I could reuse in future projects.

### Mastering AI Prompts and Models

Refining prompts became an art. With each app I built, I tweaked my initial prompt. By the tenth iteration, GPT-O would think for well over a minute every time I used it. I started by asking the large GPT-O model to architect a full spec, then dropped that plan into Sonnet 3.5 for coding. It was like having a team of expert developers at my fingertips.

### Leveraging APIs and Environment Files

I began reusing `api.js` and `.env` files across projects. This saved time and ensured consistency. I started with OpenAI's models, making use of vision, text, Whisper, and of course, the GPT series. That `api.js` file became gold. It was the foundation for robust app features.

### Overcoming Technical Hurdles

There were challenges. Installing Tailwind in VS Code was more trouble than it was worth. I relied heavily on AI guidance for concepts I didn't understand, like backend security and deployment automation. What's a Git? I wasn't sure, but GPT-O helped me navigate it. The AI explained complex concepts in simple terms.

### Achieving Milestones

I built half a dozen tools. Some were simple apps that I sold, netting low five-figure earnings. Not huge, considering my distribution reach, but it was proof of concept. I hit my $10k goal. Apps that once seemed out of reach were now within my grasp.

### Collaborating and Scaling Up

I considered bringing in a React developer to help develop more templates and review the AI-generated code for mistakes. I heard there were many of them, and they were affordable in this AI-driven era. I already had a backend developer, so I thought about roping him in to help with backend security. Together, we could scale up and improve efficiency.

### Automating Deployment

Next up was automating deployment using GitHub and Netlify. I had no idea what any of this meant, but GPT-O did. With AI's help, I set up automated deployments. It streamlined the process and saved time. The AI guided me through each step, turning complex tasks into manageable ones.

### Future Ambitions and Innovations

My goal before Christmas? To build an Apple Vision app entirely with my AI agent, straight from a voice command. Apps with a Telegram voice command, anyone? I'm looking at iOS apps next. I was entering terrain I knew nothing about, but that didn't stop me. The possibilities seemed endless.

### Reflecting on the Broader Implications

Perhaps I have no business being in these waters. Maybe, in 2025 and 2026—with agents, AI code, voice assistants, and agent-to-agent interactions—none of us are ready for what's coming next. The rapid advancements in AI are opening doors that were previously closed to non-developers like me. It's both exciting and a little unsettling.

---

### Reaching the Goal

Yes, I hit my $10k goal. I, a non-developer, used AI tools to create apps that would have cost me thousands of dollars just a couple of years ago. This experience has been a game-changer. It has empowered me, a marketer, to step into the world of app development.

### Contemplating the Future Impact

I'm excited about turning this process into an agent setup for 2025. With AI agents, voice-commanded app creation, and the potential for agent-to-agent interactions, the possibilities are endless. The lines between technical and non-technical roles are blurring. AI is democratizing app development.

### Inspiring Action

If I can do it, so can you. AI tools are lowering the barriers to entry in app development. You don't need to be a seasoned developer to build something impactful. Embrace AI and explore the possibilities beyond traditional limitations. The tools are there—you just need to take the leap.

### Final Thought

The future is coming fast. We need to adapt and be ready for what's next. Perhaps none of us are fully prepared, but with AI as our ally, we can venture into new territories. **Are you ready to take the leap?**

Article 4 - Gemini 1.5 Preview

I Challenged Myself to Code a $10k App with AI. Here’s What Happened.

**Introduction**

Have you ever dreamed of building your own app? Do you think coding is too hard to learn?  Have you seen what AI can do lately?  I'm a marketer, not a coder.  I've sold software for over ten years. I've worked with small apps and huge websites. I even have some patents!  I know what good software looks like.  I wanted to see if AI could build a $10,000 app.  Could AI do what I used to pay developers big bucks for?  The answer is surprising.

**The AI Arsenal**

If I needed a cheap app before, I’d find a cheap developer, or get creative with marketing.  But things are different now. It's October 2024. We have amazing AI tools like Cursor, Claude Sonnet, and GPT-O. A bigger GPT-O is coming soon, too! I’ve been building AI bots since GPT-4 came out in March 2023. I thought AI could code simple apps, the kind with 3-5 pages. I was right.  My first try?  I made Chrome extensions.  I just told GPT-4 what I wanted, and it did it!  But that was just the start.  Sonnet 3.5 and Cursor let me build bigger apps that run in your web browser.  I used tools like Firebase and lots of APIs.  Spoiler alert: I built apps I once paid $15,000 for!

**My AI Coding Secrets**

Here's how I did it. First, I picked a coding language: React.js with plain CSS.  I tried to use Tailwind CSS but gave up. AI makes me impatient!  Second, I save everything! Every piece of code AI makes is a lesson.  It also saves me money on computer power when I use Sonnet 3.5 (those usage limits are pricey!).  I use special files called api.js and .env that I reuse in different apps.  Speaking of APIs, I started with OpenAI's models. They have tools for pictures, text, sound, and of course, GPT. My api.js file is super helpful. Third, I use AI coding tools.  I use a big prompt (a question for the AI) and ask GPT-O to make a plan for the app. Then, I give that plan to Sonnet 3.5.  I keep making my prompt better with each app.  My first prompt is now on version ten!  GPT-O thinks for over a minute when I give it that prompt now.

**The Future of App Building (and Me)**

So far, I've made six tools.  I'm thinking about hiring a React developer to help me make more templates and check my AI-made code for mistakes. I hear there are lots of developers looking for work now, and they're not expensive. I've sold a few easy apps and made a bit of money (low five figures). It’s not a lot, but this is a huge opportunity, like AI agents! I can ignore making quick cash for now while I learn more. I have a backend developer, so I might ask him to help with security.  (What's a Git, anyway?)  I also want to automate things with GitHub and Netlify.  I don't know what those are, but GPT-O does!

**A Rich Man? A Dangerous Future?**

I hit my $10,000 goal! I’m sure I can turn this into an AI agent system by 2025.  Imagine controlling apps with your voice on Telegram!  I’m also going to try making iPhone apps next.  My Christmas goal? An Apple Vision app built by my AI agent, just from my voice commands. But am I getting in over my head?  Maybe I don’t belong here. Maybe, in 2025 and 2026, none of us are ready for what AI can do. AI code, voice assistants, agents talking to each other… it’s going to be wild.

**Conclusion**

I built a $10,000 app with AI!  It's a whole new world. Anyone can build apps now, even if they can't code.  I'm excited to turn this into an AI agent system in 2025. Imagine: Make an app, just by talking to your computer! AI is changing everything, fast. Are you ready?

Article 5 - Sonnet 3.5 Preview

Title: I Challenged Myself to Code a $10k App with AI. Here's What Happened.

Ever wonder if a non-coder could build a high-value app using only AI? As a marketer who's been in the software game for over a decade, I decided to find out. I've sold hundreds of apps, from small projects to six-figure SaaS platforms with patents. But here's the kicker: I've never written a line of code myself. So, I set myself a challenge: Could I use AI to create an app worth $10,000? Spoiler alert: I did it, and then some. Let me take you on this wild ride into the future of app development.

It's October 2024, and the AI landscape has exploded. We've got Cursor, Claude Sonnet, and GPT-O at our fingertips. Since GPT-4 dropped in March 2023, I've been building AI agents and bots, but this was different. This was about creating real, valuable software without a dev team. Crazy, right?

I started small, with Chrome extensions. Using just GPT-4 (yeah, the old version), I described what I wanted, and boom – functional extensions. But that was just the beginning. As Sonnet 3.5 and Cursor came into play, I leveled up to browser-based apps using Firebase and a bunch of APIs. And guess what? I built apps I used to pay $15k for. Mind. Blown.

Now, let me share some secrets I picked up along the way. First, stick to one language. I went with React.js and vanilla CSS. Why? Because I couldn't figure out how to install Tailwind in VS Code and got impatient. AI makes you move fast, folks.

Second, template everything. Every bit of AI-generated code that works is gold. Save it, reuse it. It'll save you time and those precious GPUs when you're burning through Sonnet 3.5 sessions. (Watch those limits!)

Third, get smart with your APIs. Start with OpenAI's models – you can do a ton with vision, text, Whisper, and the GPT series. That api.js file? It's your new best friend.

Here's a game-changer: Use GPT-O to plan, Sonnet 3.5 to execute. I write a super detailed prompt, ask GPT-O to architect the whole spec, then feed that plan to Sonnet 3.5. My initial prompt is on its tenth version now, and GPT-O thinks for over a minute each time. It's like having a senior dev and a coding wizard on speed dial.

So far, I've built half a dozen tools. I've sold a few simple apps and netted low five figures. Not bad for a non-coder, right? But I'm not stopping there. I'm thinking about bringing in a React dev to help with templates and catch any AI-generated mistakes. Word is, there are plenty of them, and they're cheap these days.

Next up? I'm eyeing iOS apps. And get this – my goal before Christmas is to build an Apple Vision app entirely with my AI agent, straight from a voice command. Crazy ambitious? Maybe. But that's where we're at in 2024.

Now, let's talk about the elephant in the room. Am I in over my head? Probably. Do I have any business swimming in these tech waters? Debatable. But here's the thing – with AI agents, voice assistants, and agent-to-agent interactions on the horizon for 2025 and 2026, none of us are really ready for what's coming next.

So, did I hit my $10k app goal? You bet. And I'm convinced this is just the tip of the iceberg. Imagine apps created with a simple Telegram voice command. Picture a world where non-techies like me can bring complex software ideas to life without writing a single line of traditional code.

But let's pump the brakes for a second. As exciting as this is, it's also a bit scary. We're entering uncharted territory here. The tools we have at our fingertips are powerful, and they're evolving faster than we can keep up. Are we opening Pandora's box? Maybe. But there's no putting this genie back in the bottle.

Here's my take: Whether we like it or not, AI is revolutionizing app development. It's lowering barriers, democratizing tech creation, and blurring the lines between marketers, founders, and developers. My journey from app seller to AI-powered app creator is just one example of what's possible.

So, what's next for you? Are you ready to dive into this AI-powered future? Whether you're a seasoned dev or a total newbie like I was, the playing field is leveling. The question isn't whether AI will change app development – it's how quickly you'll adapt to the change.

One thing's for sure: the future of app development is here, and it's powered by AI. Are you ready to build your $10k app?

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                        text: 'Year'
                    }
                }
            },
            plugins: {
                title: {
                    display: true,
                    text: 'Decrease in App Development Cost Over Time Due to AI Tools'
                },
                tooltip: {
                    enabled: true,
                    callbacks: {
                        label: function(context) {
                            return ' $' + context.parsed.y;
                        }
                    }
                },
                legend: {
                    display: false
                }
            }
        };

const myChart = new Chart(ctx, {
            type: 'line',
            data: data,
            options: options
        });
    </script>
</body>
</html>

Data3 - Table

Here is the complete code for the comparative table contrasting different elements from the article. The table fits within a **1200x600 pixels** container.

```html
<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <title>Comparative Table – Traditional vs AI-Assisted App Development</title>
    <style>
        body {
            font-family: Arial, sans-serif;
            width: 1200px;
            height: 600px;
            margin: 0 auto;
            padding: 20px;
            box-sizing: border-box;
        }

h1 {
            text-align: center;
            margin-bottom: 20px;
        }

.table-container {
            width: 100%;
            height: calc(100% - 100px);
            overflow: auto;
        }

table {
            width: 100%;
            border-collapse: collapse;
            table-layout: fixed;
        }

th, td {
            border: 1px solid #ccc;
            padding: 10px;
            word-wrap: break-word;
            vertical-align: top;
        }

th {
            background-color: #f2f2f2;
            text-align: left;
        }

.left-column {
            width: 25%;
        }

.center-column, .right-column {
            width: 37.5%;
        }

ul {
            margin: 0;
            padding-left: 20px;
        }
    </style>
</head>
<body>
    <h1>Traditional vs AI-Assisted App Development</h1>
    <div class="table-container">
        <table>
            <tr>
                <th class="left-column">Aspect</th>
                <th class="center-column">Traditional Development<br>(Before AI)</th>
                <th class="right-column">AI-Assisted Development<br>(With AI)</th>
            </tr>
            <tr>
                <td>Required Skills</td>
                <td>
                    <ul>
                        <li>Extensive coding knowledge</li>
                        <li>Expertise in programming languages</li>
                        <li>Experience with development frameworks</li>
                    </ul>
                </td>
                <td>
                    <ul>
                        <li>Minimal coding skills</li>
                        <li>Ability to use AI tools and refine prompts</li>
                    </ul>
                </td>
            </tr>
            <tr>
                <td>Development Time</td>
                <td>
                    <ul>
                        <li>Long development cycles</li>
                        <li>Time spent writing and debugging code</li>
                    </ul>
                </td>
                <td>
                    <ul>
                        <li>Accelerated development</li>
                        <li>AI generates code quickly</li>
                    </ul>
                </td>
            </tr>
            <tr>
                <td>Costs</td>
                <td>
                    <ul>
                        <li>High costs for hiring developers</li>
                        <li>Possible six-figure budgets for large projects</li>
                    </ul>
                </td>
                <td>
                    <ul>
                        <li>Reduced costs</li>
                        <li>AI replaces need for extensive development teams</li>
                    </ul>
                </td>
            </tr>
            <tr>
                <td>Tools Used</td>
                <td>
                    <ul>
                        <li>Traditional IDEs like VS Code</li>
                        <li>Manual coding and configurations</li>
                    </ul>
                </td>
                <td>
                    <ul>
                        <li>AI tools like GPT-4, Claude Sonnet 3.5, GPT-O</li>
                        <li>Automated code generation</li>
                    </ul>
                </td>
            </tr>
            <tr>
                <td>Flexibility</td>
                <td>
                    <ul>
                        <li>Changes require manual adjustments</li>
                        <li>Can be time-consuming</li>
                    </ul>
                </td>
                <td>
                    <ul>
                        <li>Easy to adjust by modifying prompts</li>
                        <li>AI can quickly regenerate code</li>
                    </ul>
                </td>
            </tr>
            <tr>
                <td>Quality of Code</td>
                <td>
                    <ul>
                        <li>Depends on developer expertise</li>
                        <li>Potential for human error</li>
                    </ul>
                </td>
                <td>
                    <ul>
                        <li>AI-generated code may contain errors</li>
                        <li>Needs review and possible cleanup</li>
                    </ul>
                </td>
            </tr>
            <tr>
                <td>Deployment</td>
                <td>
                    <ul>
                        <li>Manual setup of deployment pipelines</li>
                        <li>Requires understanding of tools like Git and Netlify</li>
                    </ul>
                </td>
                <td>
                    <ul>
                        <li>AI can suggest automated deployment setups</li>
                        <li>Less hands-on time required</li>
                    </ul>
                </td>
            </tr>
            <tr>
                <td>Reusability</td>
                <td>
                    <ul>
                        <li>Developers may create reusable code modules</li>
                        <li>Requires forethought and planning</li>
                    </ul>
                </td>
                <td>
                    <ul>
                        <li>AI encourages saving and reusing code snippets</li>
                        <li>Efficiency in building new projects</li>
                    </ul>
                </td>
            </tr>
            <tr>
                <td>Innovation</td>
                <td>
                    <ul>
                        <li>Limited by human creativity and resources</li>
                    </ul>
                </td>
                <td>
                    <ul>
                        <li>AI opens new possibilities</li>
                        <li>Non-developers can create complex apps</li>
                    </ul>
                </td>
            </tr>
            <tr>
                <td>Future Outlook</td>
                <td>
                    <ul>
                        <li>Continued reliance on skilled developers</li>
                        <li>Incremental improvements in tools</li>
                    </ul>
                </td>
                <td>
                    <ul>
                        <li>Rapid evolution of AI capabilities</li>
                        <li>Potential to revolutionize app development</li>
                    </ul>
                </td>
            </tr>
        </table>
    </div>
</body>
</html>
```

**Instructions to Use:**

- Copy the entire code block above.
- Paste it into a new file and save it with an `.html` extension (e.g., `comparative_table.html`).
- Open the HTML file in a web browser to view the comparative table.

**Note:**

- The table highlights the key differences and similarities between traditional app development and AI-assisted app development as described in the article.
- The design ensures the content fits within a container of **1200x600 pixels**, with scroll bars appearing if the content exceeds the container due to browser rendering differences.
- All code, including HTML and CSS, is contained within a single file for easy copy-pasting and use.

Data4 - SPA1

<!DOCTYPE html>
<html>
<head>
    <meta charset="UTF-8">
    <title>AI Coding Challenge Word Cloud</title>
    <style>
        body {
            margin: 0;
            padding: 0;
            overflow: hidden;
            background-color: #1a1a1a;
        }
        #wordcloud {
            width: 1200px;
            height: 600px;
            display: block;
            margin: 0 auto;
            background-color: #1a1a1a;
        }
        canvas {
            width: 1200px !important;
            height: 600px !important;
        }
    </style>
</head>
<body>
    <canvas id="wordcloud"></canvas>

<script src="https://cdnjs.cloudflare.com/ajax/libs/wordcloud2.js/1.0.6/wordcloud2.min.js"></script>
    <script>
        // List of words and their weights
        var words = [
            ['AI', 10],
            ['Coding', 9],
            ['$10k App', 8],
            ['Challenge', 8],
            ['Non-developer', 7],
            ['Code', 7],
            ['Future', 7],
            ['GPT-O', 6],
            ['Claude Sonnet 3.5', 6],
            ['OpenAI', 6],
            ['Tools', 6],
            ['Success', 6],
            ['Developer', 6],
            ['ChatGPT', 6],
            ['Cursor', 5],
            ['APIs', 5],
            ['Experiment', 5],
            ['Automation', 5],
            ['Marketing', 5],
            ['Voice Commands', 5],
            ['React.js', 4],
            ['Deployment', 4],
            ['GitHub', 4],
            ['Netlify', 4],
            ['Firebase', 4],
            ['Apple Vision', 4],
            ['Whisper', 4],
            ['DALL-E', 4],
            ['Vision Capabilities', 4],
        ];

var canvas = document.getElementById('wordcloud');

WordCloud(canvas, {
            list: words,
            gridSize: Math.round(16 * canvas.width / 1024),
            weightFactor: function (size) {
                return Math.pow(size, 2.3) * canvas.width / 1024;
            },
            fontFamily: 'Helvetica, Arial, sans-serif',
            color: function (word, weight) {
                if (weight >= 8) return '#ff4d4d';
                else if (weight >= 6) return '#ffa64d';
                else if (weight >= 4) return '#ffff66';
                else return '#b3ff66';
            },
            rotateRatio: 0.5,
            rotationSteps: 2,
            backgroundColor: '#1a1a1a',
            drawOutOfBound: false,
            shuffle: true,
            shape: 'circle',
            ellipticity: 1
        });
    </script>
</body>
</html>

Data5 - imageprompts1

1. **Fantastical & Photorealistic:**
   
   "A photorealistic image of a non-developer standing confidently amidst a swirling vortex of luminous code and AI symbols, with newly formed app icons floating around him; the scene is fantastical and dream-like, illustrating the empowerment of creating apps using AI tools without traditional coding."

2. **Split-screen & Realistic:**
   
   "A split-screen photorealistic image: on the left, traditional developers intensely typing code on multiple monitors in a cluttered office; on the right, the same person casually interacting with an AI assistant on a sleek laptop in a modern, bright workspace, with apps generating automatically on the screen—showcasing the before-and-after transformation brought by AI coding."

3. **Action-based, Scenic & Realistic:**
   
   "A realistic scene of the author speaking voice commands to a holographic AI assistant in a cutting-edge studio; around them, lines of code and app interfaces materialize in mid-air, dynamically illustrating the process of creating apps through voice interaction with AI."

4. **Visceral & Photorealistic:**
   
   "A visceral, photorealistic image of the author standing at the edge of a vast, futuristic cityscape made entirely of glowing code and digital architecture; he gazes forward with a mix of excitement and apprehension, embodying the thrilling uncertainty of the future of AI-driven coding."

5. **Action-based & Photorealistic:**
   
   "A photorealistic image of a humanoid AI assistant coding on a high-tech computer; streams of luminous code flow seamlessly from its fingertips into the screen where a complex app interface is forming, symbolizing AI handling the heavy lifting in app development."

Article Plan

**1. Suggested Title** - "I Challenged Myself to Code a $10k App with AI. Here’s What Happened." --- **2. Narrator's Direction** The narrator, a marketer with over a decade of experience in selling and commissioning software, set a personal challenge to code a $10,000 app using AI tools. Traditionally reliant on developers for creating apps—ranging from small projects to mega SaaS platforms—the narrator aims to explore whether advanced AI technologies in October 2024 can enable a non-technical founder to build high-value applications independently. The essay intends to share this journey, discuss the AI tools used, reveal secrets and strategies discovered along the way, and contemplate the future implications of AI in app development and the broader industry. --- **3. Selected Templates to Follow** Based on the transcription, the essay doesn't specify a strict structure, allowing flexibility in choosing formats. Therefore, the following three popular formats are selected: 1. **Story Narrative** - **Structure:** A personal journey detailing the challenge, experiences, successes, and reflections. - **Content:** Chronicles the narrator's journey from setting the challenge to achieving the goal, highlighting experiences with AI tools, obstacles overcome, and personal growth. 2. **How-To Guide** - **Structure:** Step-by-step guidance on using AI to code high-value apps. - **Content:** Provides practical advice, secrets, and strategies for others to replicate the success, including selecting tools, programming languages, and optimizing AI prompts. 3. **Opinion Piece** - **Structure:** An exploration of viewpoints regarding AI's impact on app development. - **Content:** Discusses the implications of AI in coding, the potential disruption to traditional development roles, and reflections on future trends and challenges. --- **4. Brainstorm Bullet Point Ideas for the Skeleton Structure** ### **Draft 1: Story Narrative** #### **Introduction (10-20%):** - Introduce the personal challenge of coding a $10k app using AI. - Mention background as a marketer with extensive experience in software sales. - Highlight the dual identity as a technical marketer and non-technical founder. - Present the question: Can AI replicate the work of high-cost developers? - Set the context of October 2024 with advanced AI tools at disposal. - Spark curiosity about the outcome of this ambitious challenge. #### **Middle (60-80%):** - Share initial skepticism and motivation behind the challenge. - Detail first attempts using GPT-4 to code simple Chrome extensions. - Describe the transition to more complex apps with Cursor and Claude Sonnet. - Highlight the use of React.js with vanilla CSS and reasons for this choice. - Discuss obstacles faced, like impatience with installing Tailwind in VS Code. - Reveal secrets such as templating and saving successful AI code. - Explain the importance of refining prompts and AI input for better results. - Mention the role of OpenAI's models and the goldmine that is the `api.js` file. - Reflect on building tools previously costing $15k and the realization of AI's potential. - Discuss considerations of bringing in a React developer for code review. - Share experiences of selling simple apps and achieving low five-figure earnings. - Contemplate the balance between short-term gains and long-term opportunities. - Express excitement about automating deployment with GitHub and Netlify. - Touch on the learning curve and reliance on AI for understanding new concepts. #### **Conclusion (10-20%):** - Recap the success of hitting the $10k goal through AI coding. - Reflect on personal growth and the paradigm shift in app development. - Pose questions about venturing into unfamiliar territory. - Discuss the broader implications for the future of the industry. - Share ambitious goals, like creating an Apple Vision app via AI voice command. - Conclude with thoughts on readiness for the rapid advancements ahead. --- ### **Draft 2: How-To Guide** #### **Introduction (10-20%):** - Present the exciting possibility of coding high-value apps using AI. - Address marketers and non-technical founders seeking to build apps. - Introduce the guide as a roadmap to achieving similar success. - Highlight personal experience as proof of concept. #### **Middle (60-80%):** - **Step 1: Setting Clear Goals** - Define the app you want to build and set a budget equivalent. - Understand the scope and functionality required. - **Step 2: Choosing the Right AI Tools** - Overview of AI coding assistants like Cursor, Claude Sonnet, and GPT-O. - Criteria for selecting tools based on project needs. - **Step 3: Selecting a Programming Language** - Recommend React.js with vanilla CSS for simplicity. - Discuss avoiding overcomplicating with tools like Tailwind initially. - **Step 4: Crafting Effective AI Prompts** - Importance of detailed and refined prompts. - Strategies for prompt iteration and improving AI output. - Example of using GPT-O for architectural planning. - **Step 5: Building and Reusing Templates** - Saving successful code snippets for efficiency. - Creating a library of templates for common features. - **Step 6: Managing APIs and Environment Variables** - Setting up `api.js` and `.env` files for OpenAI models. - Utilizing APIs for added functionality (vision, text, Whisper, GPT series). - **Step 7: Overcoming Obstacles** - Dealing with impatience and technical challenges. - Knowing when to seek help or hire a developer. - **Step 8: Testing and Refinement** - Importance of testing apps thoroughly. - Using AI to debug and optimize code. - **Step 9: Deployment Automation** - Steps to automate deployment with GitHub and Netlify. - Benefits of automation for ongoing development. - **Step 10: Planning for the Future** - Keeping abreast of AI advancements. - Preparing for more complex projects like iOS and Apple Vision apps. #### **Conclusion (10-20%):** - Encourage readers to embrace AI tools for app development. - Reiterate that non-technical individuals can achieve significant results. - Share optimism about the potential of AI in transforming industries. - Provide a call to action to start building and innovating with AI assistance. --- ### **Draft 3: Opinion Piece** #### **Introduction (10-20%):** - Make a bold statement about the transformative power of AI in app development. - Share personal experience as evidence of this shift. - Pose critical questions about the future of the software industry. #### **Middle (60-80%):** - **AI Redefining Developer Roles** - Discuss how AI tools enable non-developers to code complex apps. - Implications for traditional software developers and employment trends. - **The Accessibility Revolution** - How AI lowers barriers to entry in app development. - Potential for increased innovation and entrepreneurship. - **Quality and Efficiency Gains** - Personal anecdotes of coding $15k apps with AI assistance. - Improvements in development time and resource allocation. - **Challenges and Considerations** - Technical hurdles and the learning curve with AI tools. - Importance of human oversight for quality assurance and security. - **Future Outlook** - Speculation on AI agents handling more complex tasks by 2025. - The idea of voice-commanded app creation and its feasibility. - **Ethical and Economic Implications** - Potential for job displacement in the tech industry. - The need for adaptation and upskilling among professionals. #### **Conclusion (10-20%):** - Reaffirm the significant impact of AI on app development. - Encourage proactive engagement with AI technologies. - Acknowledge uncertainty and the need for preparedness. - Leave readers contemplating the balance between opportunity and disruption. --- **5. Research Keywords** 1. AI-assisted app development 2. Advancements in AI coding tools 3. React.js development with AI --- **6. Research News Keywords** 1. AI impact on software development industry 2. Latest trends in AI programming 2024 --- **7. Research Questions** 1. What are the most effective AI tools for coding apps in 2024 2. How is AI changing the demand for traditional software developers 3. What are best practices for using AI to ensure secure app development --- *Note: The bullet points above are brainstormed ideas intended to form the skeleton of each draft. They encompass key themes, personal experiences, and insights from the transcription, aligning with the specified article guidelines.*

All URLs Selected

Here are five URLs that might provide valuable insights and additional data for your article on coding a $10k app with AI: -------------------- 1. General overview of AI-assisted development and its potential https://www.outsystems.com/tech-hub/ai-ml/ai-assisted-development/ 2. Detailed insights and real-world applications of AI coding tools, including use cases and benefits https://www.sonarsource.com/learn/ai-assisted-software-development/ 3. Current trends in AI-enabled software development and its impact on the industry https://www.mckinsey.com/industries/technology-media-and-telecommunications/our-insights/navigating-the-generative-ai-disruption-in-software 4. Best practices and security measures for developing AI-powered applications https://www.tenable.com/blog/cybersecurity-snapshot-6-best-practices-for-implementing-ai-securely-and-ethically 5. A list of top AI coding tools in 2024, showcasing their features and capabilities https://techshark.io/blog/best-ai-coding-tools/ -------------------- These sources will provide diverse perspectives and data on AI's role in changing software development practices, offer practical advice on using AI tools, and outline security considerations crucial for your article.

All URLs Summary

I'm sorry, I can't assist with that request.

Final Article Structure

**Updated Skeleton Structure:** --- ### **Introduction (Approx. 10-20% of the Article)** 1. **Posing the Challenge:** - Open with the provocative question: *"Can a non-developer create a $10,000 app using only AI tools?"* 2. **Personal Background:** - Share the narrator's experience as a marketer with over a decade in software sales and commissioning—from small projects to six-figure SaaS platforms with patents. - Highlight the unique position as a very technical marketer yet a non-technical founder. 3. **Setting the Context:** - Emphasize the advancements in AI as of October 2024, with tools like Cursor, Claude Sonnet, and GPT-O. - Mention the narrator's prior experience building AI agents and bots since GPT-4's release in March 2023. 4. **Introducing the Personal Challenge:** - Explain the decision to set a $10k app development goal using AI, questioning whether AI can replicate the work of high-cost developers. 5. **Hooking the Reader:** - Tease the outcomes and insights gained from this experiment. - Build anticipation by hinting at surprising results and transformative implications. --- ### **Middle Section (Approx. 60-80% of the Article)** 1. **Embarking on the Journey:** - Describe initial skepticism and excitement about tackling app development without traditional coding skills. - Share the first successes using GPT-4 to code simple Chrome extensions by simply describing the desired functionality. 2. **Diving into the AI Arsenal:** - Detail the utilization of advanced AI tools like Cursor, Claude Sonnet 3.5, and GPT-O. - Discuss how these tools have evolved since GPT-4's debut, offering more capabilities and efficiency. 3. **Selecting the Right Language and Tools:** - Explain choosing React.js with vanilla CSS for simplicity and immediacy. - Mention the abandonment of Tailwind installation in VS Code due to impatience—a nod to AI influencing workflow pace. 4. **Unlocking Secrets to Efficient AI Coding:** - Emphasize the importance of templating and saving every successful AI-generated code snippet. - Discuss creating a personal library to reduce GPU usage and optimize future AI sessions with Sonnet 3.5. 5. **Mastering AI Prompts and Models:** - Highlight refining prompts with each app built, reaching a tenth iteration that prompts GPT-O to think extensively. - Share the strategy of using GPT-O to architect full specs before deploying plans into Sonnet 3.5. 6. **Leveraging APIs and Environment Files:** - Describe the reuse of `api.js` and `.env` files for efficiency across projects. - Discuss starting with OpenAI's models—utilizing vision, text, Whisper, and the GPT series—for robust app features. 7. **Overcoming Technical Hurdles:** - Reflect on challenges like installing Tailwind and how AI aids in navigating unfamiliar tech landscapes. - Admit to relying heavily on AI guidance for concepts like backend security and deployment automation. 8. **Achieving Milestones:** - Reveal building apps that previously cost $15k to develop. - Share the accomplishment of creating half a dozen tools and selling simple apps, netting low five-figure earnings. 9. **Collaborating and Scaling Up:** - Discuss considering bringing in a React developer to develop more templates and review AI-generated code for errors. - Note the perception that many developers are available and affordable in this AI-driven era. 10. **Automating Deployment:** - Explain plans to automate deployment using GitHub and Netlify. - Acknowledge a lack of understanding of these platforms but confidence in AI assistance to navigate them. 11. **Future Ambitions and Innovations:** - Share the goal of building an Apple Vision app entirely through AI agents and voice commands before Christmas. - Contemplate integrating Telegram voice commands and envisioning agent-to-agent interactions by 2025. 12. **Reflecting on the Broader Implications:** - Question whether venturing into this new terrain is prudent. - Ponder the industry's readiness for the rapid advancements in AI and the potential disruption ahead. --- ### **Conclusion (Approx. 10-20% of the Article)** 1. **Reaching the Goal:** - Recap the success of achieving the $10k app development challenge using AI. - Reflect on the paradigm shift experienced and the empowerment of non-technical individuals in tech creation. 2. **Contemplating the Future Impact:** - Express excitement about turning this process into an agent setup for 2025. - Discuss the potential of AI agents, voice-commanded app creation, and the uncharted waters ahead. 3. **Inspiring Action:** - Encourage others to embrace AI tools to explore possibilities beyond traditional limitations. - Suggest that with AI, barriers to entry in app development are significantly lowered. 4. **Final Thought:** - Conclude with a thought-provoking statement on the necessity to adapt in the face of rapid AI advancements. - Leave readers pondering their own readiness for what's coming next in this AI-driven future. --- This structure incorporates key elements from your initial transcription, highlights personal experiences, insights, and reflects on the transformative potential of AI in app development. It follows the guidelines provided and is designed to engage readers throughout the article.

Articles

Article 1 - chatgpt-4o-latest

Article 2 - O1 Mini

Article 3 - O1 Preview

Article 4 - Gemini 1.5 Preview

Article 5 - Sonnet 3.5 Preview

https://static.aiz.ac/distro/chart-1728068934.html

https://static.aiz.ac/distro/table-1728068934.html

https://static.aiz.ac/distro/spa-1728068934.html

Data1 - Mermaid

Data2 - Chart

Data3 - Table

Data4 - SPA1

Data5 - imageprompts1

Article Plan

All URLs Selected

All URLs Summary

Final Article Structure

Mermaid1

Chart.js 1

Final Article Structure

Final Article Structure

Final Article Structure