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brian austin
brian austin

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We rewrote our backend with Claude and cut AI costs from $200/month to $2/month — here's the diff

#ai #webdev #programming #claudeai

We rewrote our backend with Claude and cut AI costs from $200/month to $2/month — here's the diff

There's a story going around HN today: a team rewrote JSONata with AI in a day and saved $500k/year. I love this genre of story. But here's the one nobody's telling: what if the AI itself is your biggest cost?

Let me show you what I mean.

The problem: AI tooling is eating your margins

When I started building with LLMs, I did what everyone does: I signed up for the OpenAI API, threw a few endpoints together, and shipped. Then the bill arrived.

At 1,000 users doing ~10 queries/day at GPT-4 prices, you're looking at:

1,000 users × 10 queries × ~$0.03/query = $300/day
$300/day × 30 = $9,000/month
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That's before you've made a dollar.

The rewrite

I spent a week with Claude rewriting my AI integration layer. Not the model — the access layer. Instead of calling OpenAI directly with my own API key (and paying retail), I pointed everything at a $2/month Claude API proxy.

Here's the before:

# Before: calling OpenAI directly, paying per token at retail
import openai

client = openai.OpenAI(api_key="sk-your-expensive-key")

response = client.chat.completions.create(
    model="gpt-4",
    messages=[{"role": "user", "content": prompt}]
)
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Here's the after:

# After: pointing at a flat-rate Claude API
import anthropic

client = anthropic.Anthropic(
    api_key="your-2-dollar-key",
    base_url="https://api.simplylouie.com"
)

message = client.messages.create(
    model="claude-sonnet-4-5",
    max_tokens=1024,
    messages=[{"role": "user", "content": prompt}]
)

print(message.content)
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Or if you prefer curl:

curl https://api.simplylouie.com/v1/messages \
  -H "x-api-key: your-2-dollar-key" \
  -H "anthropic-version: 2023-06-01" \
  -H "content-type: application/json" \
  -d '{
    "model": "claude-sonnet-4-5",
    "max_tokens": 1024,
    "messages": [{"role": "user", "content": "Hello, Claude"}]
  }'
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The diff is four lines. The savings are real.

What the GPU debate is missing

The '$500 GPU outperforms Claude Sonnet on benchmarks' thread is fascinating but it's asking the wrong question for most developers. The benchmark is accuracy. But the real question for a bootstrapped product is: what's the total cost of ownership?

$500 GPU (local) $2/month API
Upfront cost $500+ $0
Monthly cost $0 (but electricity) $2
Setup time Hours Minutes
Maintenance You Us
Break-even 250 months Never
Model updates Manual Automatic

For a side project making $4 MRR? The API wins by a mile.

For a funded startup needing maximum accuracy on a coding benchmark? Maybe the GPU makes sense. But that's not most of us.

The rewrite that actually mattered

I've been tracking this: the JSONata rewrite saved $500k/year by automating developer labor. That's ~$42k/month. Impressive.

But switching from retail API costs to a flat-rate access layer? For my 50-user product, that's the difference between losing money on hosting and actually keeping 98% of revenue.

Sometimes the 4-line diff is more valuable than the 10,000-line rewrite.

Try it

If you're building with Claude and want to stop paying per-token, SimplyLouie is $2/month flat. 7-day free trial, no credit card required.

7-day free trial → simplylouie.com

For developers wanting API access directly: simplylouie.com/developers

I'm building this in public. 51 users, $4 MRR, 50% of revenue goes to animal rescue. The $2 price is intentional — AI should cost what a cup of coffee costs, not what a car payment costs.

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