Why the $200 Coder Broke Your App (And Why I Charge 3x More to Fix It)

The hidden cost of “just throwing it into ChatGPT.”

The Mirage: The dangerous belief that AI coding is a vending machine.

“Why is this so expensive? My competitors charge $200. Can’t you just ask ChatGPT to write the code?”

This is the question that haunts every academic consultant in 2026. And prima facie, I understand the scepticism. If I can upload a prompt to Gemini or Claude and get 500 lines of Python back in 10 seconds, why am I charging you 3x the market rate?

Because there is a difference between “AI Slop” and “Engineered Software.”

The $200 “Codingo” Disaster

Some of you might know “Codingo” — the service that famously charges $200 to churn out assignments.

A student client came to me in a panic. He had hired Codingo for his web app module. On paper, it was a steal. In reality, it was a catastrophe.

The code Codingo delivered was what we in the industry call AI Slop — raw, uncurated output from a generic LLM. I took one look at the code, and it was objectively shit. Low-quality, no structure, broken logic.

• The database connections were brittle.
• The UI was broken.
• The security was nonexistent.

When he submitted it, it collapsed. He failed his module. He had to re-module.

That $200 didn’t buy him a solution; it bought him a crisis.

The Tooling Gap: Gemini UI vs. Project Athena

The client’s misconception — and perhaps yours — is that professional developers just “throw files into Gemini UI.”

If it were that easy, you wouldn’t need me.

Real engineering doesn’t happen in a chat window.

• Amateurs use Gemini UI.
• Professionals use IDEs like Cursor and Claude Code.
• I run my IDE through a customised program called Project Athena.

Project Athena isn’t just a chatbot or a wrapper. It is a private repository on my desktop (backed up on GitHub) that condenses hundreds of hours of training data with me — my coding style, my architectural preferences, my debugging heuristics. When I generate a first draft through Antigravity, it isn’t “generic code” — it is a nuanced, contextualised foundation that no public model can replicate.

The Trap of the $400 Quote

When the client brought this rescue mission to me, my internal valuation engine pegged it at $500 — $600.

But, being my first time handling a full-stack web app project, I hesitated. I thought, “I have Athena. I have the tools. I can speedrun this.”

So I quoted $400. The client happily paid, thinking he got a deal.

Oh boy, was I wrong.

Even with Project Athena giving me a 10x head start, the work had just begun.

The Reality: AI generates chaos (left). A Senior Engineer’s architect’s order (right).

The “Whole Night” Reality: Generation is 5%, Iteration is 95%

Even after Antigravity generated the initial code, my job was far from over. The 5% is the generation. The 95% is Testing, Debugging, and Iteration.

For that “simple” $400 project, I spent the entire night in the trenches:

1. Testing the Output: AI makes confident mistakes. Each generated file had to be run, and each error had to be caught.
2. Pointing Out Flaws: Edge cases, broken routes, uncaught exceptions — I had to find them all before the client ever saw the code.
3. Debugging: Manually tracing logic errors that the AI was oblivious to.
4. Refining the UI: “Make it pretty” is a prompt; actual UX design is a discipline.
5. Re-Iterating: Feed the errors back into Athena, apply changes, test, and repeat until the codebase was 100% solid.

The Real Product: After-Support is Included

And here is the kicker that most clients don’t understand. After I delivered the final, polished repository, the job still wasn’t done.

Why? Because my service isn’t just “deliverables.” It’s a full package.

The client had questions. “How do I run this locally?” “Why did we use MongoDB here?” “What does this function do?”

I had to become his teacher. I had to ensure he understood the code well enough to defend it. That after-support is included in the pricing.

If I had just dumped the files on him (like Codingo did), he would have been lost the moment something broke. And if his professor asked him a single question about the implementation, he would have frozen.

The Lesson: Fair Pricing for Real Value

The lesson I learned — and the reason I am writing this — is simple: I will never underquote again.

When I quote $600, I am not ripping you off. I am engaging in Fair Value Pricing.

You aren’t paying for the keystrokes. You can get those for free. You are paying for:

1. The System (Project Athena) that architects a superior, contextualised foundation.
2. The Expertise that spends all night testing, debugging, and iterating until it’s airtight.
3. The After-Support that ensures you actually understand what you’re getting.

The Value: You don’t pay for the autopilot. You pay for the Pilot who lands the plane when it fails.

If $600 sounds “too expensive” because “you just let ChatGPT do it all,” I invite you to bookmark this article. When the $200 code breaks at 3 AM and you don’t know why, you’ll understand exactly what you’re paying for.

Winston Koh is the creator of Project Athena and a Full-Stack Developer leveraging Agentic AI to build sovereign systems.