I Spent $638 on AI Coding Agents in 6 Weeks.
Key topics
Context: I'm an Founder & CTO building an AI-First CRM product.
Here's what happened:
October: Started the month thinking "I'll stay within the Pro limits, no problem." By mid-month, Cursor hit me with a $280 invoice. By month end? $348.56 total in on-demand charges. I literally maxed out the $400 limit.
November: It's only November 12 and I've already been invoiced $289.38:
Cost per request: Claude 4.5 Sonnet Thinking ranges from $0.02 to $0.06 depending on context size. Doesn't sound like much until you realize you're hitting it 200+ times per day.
I tried 7 different models (GPT-5, Gemini 2.5 Pro, Cheetah, etc.) thinking I'd save money. Claude still ate 85% of my budget because, honestly, it's the best.
Am I more productive? Absolutely. Is it worth $638 every 6 weeks? Idk. That's $5,500+ annually just for code assistance.
So I'm curious:
What are YOU spending? Am I an outlier or is this the new normal?
Have you changed behavior to cut costs? (Using faster models? Being more selective? Bringing your own API keys?)
At what price point would you stop? $100/month? $500? $1000?
Is anyone actually staying within the included limits? Or is that just marketing?
I feel like we're in this weird phase where the value is obvious but the pricing model hasn't stabilized.
Would love to hear how others are navigating this.
The author spent $638 on AI coding agents in 6 weeks and is questioning whether it's worth the cost, sparking a discussion on cost management and productivity gains.
Snapshot generated from the HN discussion
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6m
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- 01Story posted
Nov 13, 2025 at 7:51 AM EST
about 2 months ago
Step 01 - 02First comment
Nov 13, 2025 at 7:57 AM EST
6m after posting
Step 02 - 03Peak activity
6 comments in 0-1h
Hottest window of the conversation
Step 03 - 04Latest activity
Nov 13, 2025 at 11:07 AM EST
about 2 months ago
Step 04
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$638/6 weeks won't make me broke, but here's my main issue: for me it's about the value-to-token ratio feeling off.
What bugs me most is that many of those 340M tokens feel wasteful? Like the LLM will use 50k tokens exploring dead ends before finding a solution that could have been expressed in 5k tokens. The productivity gain is real, but it feels like I'm paying 10x more than what should be "fair" for the actual value delivered.
Maybe this is just the current state of AI coding - the models need that exploration space to get to the answer. Or maybe I need to get better at constraining the context and being more surgical with my prompts.
For me as a founder, it's less "can I afford this" and more "does this pricing model make sense long-term?" If AI coding becomes a $5-6k/year baseline expense per developer, that changes a lot of unit economics, especially for early-stage companies.
Are you finding Claude Code Max more token-efficient for similar tasks, or is it just easier to stomach because the billing is flat?
I did experiments with Claude Sonnet and Opus and also with Gpt-5, the latter via my Perplexity subscription. My experience with Claude was mixed; most output required significant re-work which mostly consumed the time savings enabled by Claude. In contrast, Gpt-5 was able to generate code for several complex problems and made different transpilations for me, and the generated code usually compiles and correctly runs up front, all covered by my Perplexity subscription.
> What bugs me most is that many of those 340M tokens feel wasteful? Like the LLM will use 50k tokens exploring dead ends before finding a solution that could have been expressed in 5k tokens. The productivity gain is real, but it feels like I'm paying 10x more than what should be "fair" for the actual value delivered.
Yes, there is an apparent fluctuation in pricing for said tokens/credits/etc.. and they are just finding the sweet spot.
I primarily use the https://www.warp.dev/ terminal and they have just released a new plan which outwardly states lower cost per request.
They mentioned 'At full usage, the plans didn’t scale sustainably'. This is encouraging to know.
Right now, I'm looking around and trying out. Nice read, thanks.
Key Findings from Your Cursor Usage Here are the most interesting insights from your usage data:
Cost Summary
Total Cost: $928.45 over 70 days
Average per Request: $0.06
Cost per Task (Request): Ranges from $0.00 to $2.78, with 65.7% costing under $0.05
Projected Monthly Cost: ~$416 (based on average daily spend of $13.86)
Request Patterns
Requests per 5 Hours: Average 70.7, ranging from 1 to 451
Average Time Between Requests: 6 minutes 33 seconds
Median Time Between Requests: Just 13 seconds (shows bursts of activity)
Peak Activity: 1-2 PM (10.4% of all requests at 1 PM)
Busiest Day: Saturday with 21.7% of requests
Token Efficiency
Average Tokens per Request: 83,371 tokens
Median Tokens per Request: 38,342 tokens
Average Output per Request: 876 tokens
Cache Hit Rate: 88.8% (excellent! saves money)
Cost per 1,000 Tokens: $0.0009 (very efficient due to caching)
Cost per 1,000 Output Tokens: $0.14
Notable Stats
Most Expensive Request: $2.78 using 6.8M tokens (mostly cached)
Total Hours of Active Usage: 1,692 hours (~9 requests/hour)
Most Used Models: claude-4.5-sonnet-thinking, claude-3.5-sonnet, and others
Your cache hit rate of 88.8% is excellent and is saving you significant costs! Without caching, your costs would be much higher.