I've switched AI coding tools **five times** in the past year. Codex → ChatGPT (a step back) → Cursor → Google Antigravity → Claude Code (Pro → Max). Each time, I clicked "This is it" and hit the payment button, and each time, I learned something. Now, I'm spending **₩250,000-₩300,000 per month** on AI, and I'm figuring out how to make that into a side income.
This post is that **honest journey** — why certain tools didn't work, what the real turning points were, and why I keep paying for expensive tools despite knowing the cost.
I'm a solo developer in Korea building AI services. I only write about experiences based on **personally paying for and using** these tools. (My tool/price evaluations are subjective, based on my own usage environment.)## 1. One Year, Five Tool Switches — At a Glance
| Timeline | Tool | Payment | Conclusion |
|---|---|---|---|
| 2025.05 | **Codex** | ₩200,000 | Didn't follow prompts, couldn't even find the source of errors → retreated to ChatGPT |
| 2025.12 | **Cursor** | — | First "it works" feeling. OK for simple tasks, but I had to guide it for complex ones |
| 2026.03 | **Google Antigravity** | ₩180,000 | Better performance but limitations in memory/agent capabilities + Claude API double-billing trap |
| 2026.04 | **Claude Code (Pro)** | ₩200,000 (Additional Payment) | Top-notch problem-solving but depleted quickly → additional payment hell |
| Current | **Claude Code (Max)** | ₩180,000/month | Settled. Using it well, but a fixed monthly cost |
2. 2025.05 — Codex, The First ₩200,000 Failure
My journey with "Vibe Coding" started in May 2025, with a **₩200,000 payment for Codex**. YouTube was flooded with videos claiming "AI will write all your code." But when I actually uploaded code and gave it tasks — **for web development, it simply didn't generate what the prompts asked for.** What was even more frustrating was that I couldn't even find **where the errors were** on each page, just going in circles.
The conclusion was anticlimactic: **"If I'm going to use Vibe Coding, I might as well just use ChatGPT directly."** So, I went back to ChatGPT for a while. Although my first tool was a failure, I learned something: **"Just let the AI figure it out" doesn't work.**
3. 2025.12 — Cursor, The First "It Works" Moment
Six months later, I tried Cursor, and this time I felt a **definite improvement**. When developing at my company, **it was quite good for implementing simpler things.** It was the first time I thought, "AI coding is actually possible."
However, there were clear limitations. **When delving into more complex development, I had to ask multiple times, and it was only through me guiding the direction** that we could solve the problems. As the tool got better, the realization that **"I need to set the direction"** became even clearer.## 4. 2026.03 — Google Antigravity, and the 'Double Billing' Trap
In March 2026, I switched to Google Antigravity. I moved because **its performance was clearly better than Cursor**. However, when it came to **agent-level development or game development**, issues surfaced — I had to ask multiple times, but it **couldn't properly remember past context**, and the solutions weren't clean. (This was after I had paid ₩180,000.)
Here's where I found something interesting. When I switched the model to Claude within Antigravity, it solved problems properly. But after a few uses, it **quickly exceeded its limits**. So, I **connected my own Claude API** and instructed it, "If Antigravity can't solve it, use my Claude API to get it solved." But then — it was a **double-billing** structure (Antigravity subscription + my API calls). I knew the key to performance was the **model (Claude)**, but the method was inefficient.
5. 2026.04 — Claude Code, Through the Burnout Hell to Max
So, in April 2026, I switched directly to **Claude Code**. I decided it was better to use that Claude model without double-billing.
Initially, I started with **Claude Pro**, but as expected, with its good performance, it **depleted very quickly**. This led to additional payments. It felt like I hadn't used it much, but I ended up spending an **additional ₩200,000 that month**. Eventually, I ended up subscribing to **Claude Max** and have been using it **effectively** ever since.
The tool changed five times, but the lesson learned was the same as before — the core of solving problems wasn't the tool's name but **"the power of the model × my ability to guide the direction."**
6. The Reality of the Cost — ₩250,000-₩300,000 Per Month
Let me be honest and share the numbers. This is what I'm spending each month:
**Claude Max ₩180,000 + GCE Cloud + Separate AI API Calls** = approximately **₩250,000-₩300,000 per month.** I have almost no income yet, but I have fixed expenses. That's why I'm constantly thinking and searching for **how to turn this into a side income.**
7. An Honest Conclusion — A ₩300,000 Question
Looking back, though the tools changed five times, the lesson converged into one:
**The names of AI coding tools keep changing. But what solves the problem has always been the same — a powerful model × a person who guides the direction. AI is a tool to amplify skills, not replace foundation and judgment.**
And that amplification comes with a realistic price tag of **₩300,000 per month.** This is my mindset:
**Do your best first (not keeping up is a bigger loss). Then, create a way to afford that cost.**
This blog, the Riel chatbot, and all the development logs I share — are essentially **the process of finding an answer to that ₩300,000 question ("How can I afford to keep going?").** Can the cost of keeping up with AI be offset by the things created *with* AI? I'll continue to document that experiment.
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