The API Cost Trap: Why AI-Generated Code Can Blow Up Your Cloud Bill

Imagine: You open your Google Cloud console in the morning and instead of the usual €150, you see €1,800 in charges — in a single day.

That happened to us. And today I'm sharing what went wrong, how we fixed it in two hours, and what you can learn before the same thing happens to you.

What Happened?

In our dispatch AI for transport companies, we have a feature that monitors truck positions in real time. Every few minutes, we query the GPS location and calculate via Google Maps how long until the truck reaches its next stop.

This ran smoothly — €150 per month, budgeted, all good.

Then we added two new features: more frequent updates for our clients. The dispatch plan view now refreshed more often.

Two days later: €1,800 in projected costs. A tenfold increase. Annualized: over €20,000.

The Bug: We Asked Google Even When There Was Nothing to Ask

The problem was simple: we queried Google Maps on every update — even when the truck was sitting at a red light, parked in a lot, or hadn't moved for 30 minutes.

Every request costs money. The increased frequency made costs explode.

The Fix: 2 Hours, 100 Lines of Code

We went into the codebase with Claude Code and added a simple check:

Before asking Google: Has the truck actually moved significantly?

If the last GPS point is identical to the one from a minute ago — no request. If the truck has been stationary for 30 minutes — no request.

The result:

• Less than 100 lines of code
• No loss in data quality
• Costs down to ~€250/month (from €1,800)

Clients notice no difference. We save over €18,000 per year.

5 Lessons Everyone Should Know

1. API Costs Are Invisible Time Bombs

You don't see these costs in the code — there's just an innocent API call. You don't see them in testing — 100 test runs don't register. You only see them on the invoice. And by then it's often too late.

2. API Integration ≠ API Usage

Connecting an API is relatively easy. The art lies in:

• When do I use the API?
• How often do I call it?
• Can I cache results?

That's what determines the costs.

3. Monitoring Is Not Optional

We caught it because we were paying attention. Many teams never check the cloud console — they only find out when accounting calls.

4. AI Doesn't Optimize for Cost

This is the blind spot: When you let AI write code, it optimizes for "it works" — not for "it's cost-efficient."

The more we trust AI-generated code, the more important it becomes to expand code reviews to include API cost considerations.

5. Alternatives Exist

We've since switched from Google Maps to TomTom. Just because the first solution works doesn't mean it's the best one.

OpenStreetMap is free but often insufficient for precise logistics applications. You need to know the trade-offs.

4 Steps You Can Take Today

1. Set Budget Alerts — Now.

Every cloud provider has this: Google Cloud, AWS, Azure, OpenAI API.

If you normally pay €100/month:

• First alert at €50
• Second alert at €75

If the €50 alert triggers after 3 days, you know something's wrong.

2. Audit Your Code for API Calls

Everywhere you call external APIs, ask yourself:

• Does it need to be this frequent?
• Can I cache this?
• Can I check internally whether the request is even necessary?
• Is there batching (bundling multiple requests)?

3. Evaluate Alternatives

Make a list of your API costs. Which services drive the costs? Are there cheaper alternatives with comparable quality?

4. Build Cost Awareness Into Code Reviews

New mindset shift: In code reviews, don't just ask "Does it work?" and "Is it secure?" but also:

What does this cost if load increases tenfold?

AI has no cost awareness. We need to bring that ourselves.

Why I'm Sharing This Publicly

My LinkedIn post about this got over 60,000 views. That shows: many people know this problem — or fear it.

The uncomfortable truth: The more we automate, the more APIs we use. The more AI we deploy, the less visibility we have over the code.

Complexity isn't decreasing — it's increasing.

But with the right tools and the right mindset, it's solvable. For us, it was 2 hours and 100 lines of code.

The difference between €150 and €20,000 per year wasn't luck — it was paying attention.

Please do the same. Your cloud bill will thank you.