Microsoft reports AI is more expensive than paying human employees (opens in new tab)

Active discussion on primary source:

https://news.ycombinator.com/item?id=48238896

(Note article says "Microsoft has reportedly begun canceling most of its direct Claude Code licenses, according to The Verge.")

The title seems misleading, and reading the article explains the reason more clearly. There's nonsense OKR's and objectives at these companies to burn as many tokens as possible. It turns out that when you make a metric out of token usage, it unsurprisingly ends up becoming extremely expensive.

Inference is affordable, and you don't need a SOTA proprietary model to get a lot of use out of this technology. While you likely will still need a human engineer for quite a while longer, I don't agree that some number of humans + an LLM is going to be (or will ever remain) more expensive than just hiring more humans.

The premise of this article is incorrect - MS isn't cancelling Claude code internal usage because of AI costs too much, they're cancelling it because GitHub copilot is the compete product and they want their employees to use their product.

It's the same reason Teams got so much attention during lockdown.

Literally nowhere in the article does Microsoft report AI is more expensive than paying human employees.

The 'tokenmaxxing' trend is probably the more inane ideas emanating out of this whole AI wave. It goes in the opposite direction of efficiency and productivity maximization. Yet, it has wide acceptance.

Microsoft cancelled Claude because they need to dog food Copilot since it sucks. This was acknowledged internally and it’s not a secret.

It is probably more expensive for Microsoft now since the Anthropic tokens were subsidized.

The usage of AI has to be put in context for cost analysis.

A lot of people I see are using AI to beautify their documents, their slack conversations, emails, generating big enough documents with small prompts. Sending a slack message or email should not have required AI within the company. Its wastage of resources and time, just to make it sound better without changing much of the meaning.

Burning tokens is as easy as throwing dollars in a furnace. Token usage is not a good measure of productivity. Problem is nobody has really been able to figure out how to gauge productive AI engagement. Are your developers maximizing productivity or are they burning tokens or resisting change.

AI is not more expensive than paying a human employee. AI is not capable of replacing a human employee yet so the premise of the title is wrong.

No! - me after reading the title. I am unable to hire any more interns and junior devs. Simply because there is no way I can justify the time and money spent behind them. Money is not the issue - time taken to make them productive is not worth now.

For MSFT: Just download DeepSeek locally and use it.

Or train your own power efficient stack.

>> Microsoft has reportedly begun canceling most of its direct Claude Code licenses

Hearsay information and click bait.

AI isn't expensive.

Opus is expensive. And almost always unnecessary.

reminds me of "The Feeling of Power" by Isaak Asimov

Makes me feel good about my career. Upvote

Somehow this 'ai companies will never be profitable' is believed by so many. It's often used by those who don't like AI. There is no doubt that ai is the most lucrative business currently out there. It will only get better. Faster hardware, better algorithms

Is that why GitHub is always down?

Have you tried closing another strait?

For now.

When you unleash it without a plan or discipline, they are correct.

With discipline, it’s an aggregator.

https://devarch.ai/

Say AI is very expensive and costs a lot. What happens when no one can or is not willing to actually do the work manually?

What if companies both don't see a large return on investment, and at the same time can't reduce their AI spend?

Taalas: https://taalas.com/products/

They've made a hardware LLM that reaches over 14k TPS on Llama 3.1 8B, and you can try it here: https://chatjimmy.ai/

So clearly hardware LLMs are the future, and the cost will be drastically reduced. But I know that all the AI labs want to create a perception of high prices forever.