Sources and leaks from Amazon, Adobe, Atlassian, Citi, and more show what is really happening with AI right now: companies are trying to rein in AI use as costs spiral out of control.
Something I’ve been noticing recently is that while the cost per token on specific models hasn’t gone up, the provided interfaces for using those models are starting to chew up significantly larger numbers of tokens for the same tasks that used fewer tokens with older versions of the interface software just a few months ago. Likely the interfaces are applying more expensive guardrail prompts and charging the end user for those tokens — but the end result is that it costs 4x as much to get the same work done.
My CLAUDE.md file bloated significantly. It tried to load unnecessary skills and would retain throughout the whole session. Fixing that, maintaining good wikis and using clear often really helped fixed my personal token burn.
When you use the /init command in claude code, it’ll scan your whole project and write a CLAUDE.md, which is basically an overview of the project contents and architecture that it uses as context when responding to queries.
Consider each session with Claude a new employee. Your Claude.md file is what it knows and how it acts out the gate. You can save memory to it or save directory links so it knows where or how to look for something.
LLMs generally work in one way. They get the prompt and give an answer. CLAUDE.md, system promp, rules, memory, tool defintions, mcps are different ways to prefix your prompt with extra information or context.
Skills, or plugins, are a way to inject less information until is needed (you can think about them as prefixing your prompt with “if you are asked about pizzas, add to context separate file pizza.md”).
What you could add to CLAUDE.md depends on what you’re doing. Generally it should be context LLM cannot infer relevant to all/most task performed in given project.
It’s added in every chat you start with Claude for that project. It’s useful for including context specific to your project that it couldn’t otherwise know. High level stuff like what it’s for, but also details about how the folders are organized. This saves time and tokens from rescanning the whole thing every time.
That’s exactly what it’s perfect for. If you go further and detail the intent of the project and give a high level overview of the architecture, it’s even better at inferring what needs to be done without a bunch of expensive file reads and asking you repetitive questions
Something I’ve been noticing recently is that while the cost per token on specific models hasn’t gone up, the provided interfaces for using those models are starting to chew up significantly larger numbers of tokens for the same tasks that used fewer tokens with older versions of the interface software just a few months ago. Likely the interfaces are applying more expensive guardrail prompts and charging the end user for those tokens — but the end result is that it costs 4x as much to get the same work done.
My CLAUDE.md file bloated significantly. It tried to load unnecessary skills and would retain throughout the whole session. Fixing that, maintaining good wikis and using clear often really helped fixed my personal token burn.
What do you use that file for? I see Claude.md thrown around and I’m a bit curious.
When you use the /init command in claude code, it’ll scan your whole project and write a CLAUDE.md, which is basically an overview of the project contents and architecture that it uses as context when responding to queries.
Consider each session with Claude a new employee. Your Claude.md file is what it knows and how it acts out the gate. You can save memory to it or save directory links so it knows where or how to look for something.
LLMs generally work in one way. They get the prompt and give an answer. CLAUDE.md, system promp, rules, memory, tool defintions, mcps are different ways to prefix your prompt with extra information or context.
Skills, or plugins, are a way to inject less information until is needed (you can think about them as prefixing your prompt with “if you are asked about pizzas, add to context separate file pizza.md”).
What you could add to CLAUDE.md depends on what you’re doing. Generally it should be context LLM cannot infer relevant to all/most task performed in given project.
It’s added in every chat you start with Claude for that project. It’s useful for including context specific to your project that it couldn’t otherwise know. High level stuff like what it’s for, but also details about how the folders are organized. This saves time and tokens from rescanning the whole thing every time.
Oh, thanks! That’s kind of neat, like not having to type “I’m on godot 4, c#” every time you ask about some quirk.
That’s exactly what it’s perfect for. If you go further and detail the intent of the project and give a high level overview of the architecture, it’s even better at inferring what needs to be done without a bunch of expensive file reads and asking you repetitive questions
The models are evolving. Everything uses multi modal in the bavkend, eating up more and more tokens for the same task.
I switched to caveman on Claude Code. It cuts the token count; it’s the same output, and it appears to me to be faster as well.