once upon a time - engineers often had to concern themselves with datacenter bills, cloud bills, and eventually SaaS bills. We'll probably have 5-10 years of being concerned about AI bills before the AI expense is trivial compared to the human time.
100k/mo on cloud watch corresponds to a moderately large software business assuming basic best practices are followed. Optimization projects can often run into major cost overruns where the people time exceeds the discounted future free cash flow savings from the optimization.
That being said, a team of 5 on a small revenue/infra spend racking up 100k/mo is excessive. Pedantically, cloud watch/datadog are SaaS vendors - 100k/mo on Prometheus would correspond to a 20 node SSD cluster in the cloud which could easily handle several 10s of millions of metrics per second from 10s of thousands of metric producers. If you went to raw colocation facility costs - you’d have over a hundred dual Xeon machines with multi-TB direct attached SSD. Supporting hundreds of thousands of servers producing hundreds of millions of data points per second.
Human time is really the main trade-off.
You're like in the top 0.05% of earners in the software field.
Of course, if you save 10 hours per month, the math starts making more sense for others.
And this is assuming LLM prices are stable, which I very much doubt they are, since everyone is price dumping to get market share.
Nobody is investing half a trillion in a tech without expecting a 10x return.
And fairly sure soon those $20/month subscriptions will sell your data, shove ads everywhere AND basically only allow you to get that junior dev for 30 minutes per day or 2 days a month.
And the $200/month will probably be $500-1000 with more limitations.
Still cheap, but AI can't run an entire project, can't deliver. So the human will be in the loop, as you said, so at least a partial cost on top.
You can use these models through Claude Code; I do it everyday.
Some developers are running smaller versions of these LLMs on their own hardware, paying no one.
So I don’t think Anthropic and the other companies can dramatically increase their prices without losing the customers that helped them go from $0 to $4 billion in revenue in 3 years.
Users can easily move between different AI platforms with no lock-in, which makes it harder to increase prices and proceed to enshitify their platforms.
And even for FAANG, an SDE for them in Spain makes 60-100k total comp, not 400k.
That's why you don't pay the yearly license for anything at this point in time. Pay monthly and evaluate before each bill if there's something better out already.
Nope.
More open models ship everyday and are 80% cheaper for similar and sometimes better performance, depending on the task.
You can use Qwen-3 Coder (a 480 billion parameter model with 35 billion active per forward pass (8 out of 160 experts)) for $0.302/M input tokens $0.302/M output tokens via openrouter.
Claude 4 Sonnet is $3/M input tokens and $15/M output tokens.
Several utilities will let you use Claude Code to use these models at will.