Seriously, why can't huge companies like OpenAI and Google produce documentation that is half this good??
https://api-docs.deepseek.com/guides/thinking_mode
No BS, just a concise description of exactly what I need to write my own agent.
https://api-docs.deepseek.com/guides/thinking_mode
No BS, just a concise description of exactly what I need to write my own agent.
Western Models are optimizing to be used as an interchangeable product. Chinese models are being optimizing to be built upon.
They are developing their moats with the platform tooling around it right now though. Look at Anthropic with Routines and OpenAI with Agents. Drop that capability in to a business with loose controls and suddenly you have a very sticky product with high switching costs. Meanwhile if you stick with purely the ‘chat’ use cases, even Cowork and scheduled tasks, you maintain portability.
Now that you’re winning, others start cloning your API to siphon your users.
Now that you’re losing, you start cloning the current winner, who is probably a clone of your clone.
Highly competitive markets tend to normalize, because lock-in is a cost you can’t charge and remain competitive. The customer holds power here, not the supplier.
Thats also why everyone is trying to build into the less competitive spaces, where they could potentially moat. Tooling, certs, specialized training data, etc
But so much investment in their platforms, not just their APIs?
Example: the second sentence on the first page says “softwares” but “software” is a mass noun that cannot be pluralized.
Example: the third page about tokens has some zipped code to “calculate the token usage for your intput/output” and obviously “intput” should be “input” but misspelled.
As a company that produces LLMs, they could have even used their own LLM to edit their documentation to fix grammar issues, and yet they did not.
Maybe I’m just extra sensitive to grammar and spelling issues but this kind of lack of attention to detail is a huge subconscious turnoff. I had to fight my urge to close the tab.
I constantly see and hear this mistake from actual humans too.
It's fairly ironic that your own comment contains run-on sentences, speculative claims and phrasing peculiarities like "could have even" instead of "could even have". Perhaps you are less sensitive to this than you think!
It's strange that you criticise "could have even" when it is a phrasing clearly being used for emphasis. "Could even have" makes no clearer sense in context.
No irony detected.
But it’s okay. HN comments aren’t supposed to be high quality anyways. I know mine aren’t. But the official product documentation ought to be.
Between you, me, and the Deepseek team, so far as I'm aware, only one entity has caused the Western frontier model companies to panic by delivering an open model that competes far more cheaply, to the point where people are running versions of it at home.
So they spelled software wrong. So what? Outside of this being the mental equivalent of a too-scratchy-sweater for the kinds of people sensitive to that sort of thing, I don't see why it matters.
Those of us that have spent a lot of time programming with non native English speakers (the majority of software engineers on earth) have learned long ago that English ability has no correlation with engineering ability.
If it tickles anyone's subconscious feelings, it would be their internal guiding myth of exceptionalism. With their recent forays into authoritarianism, it's becoming ever harder to paper over the reality.
I despise American exceptionalism myself. This is entirely an issue about the quality of the language, not the nationality of the person behind it.
I read OpenAI or Anthropic's documentation nowadays and it's just so full of useless junk and self-congratulation that makes it a miserable experience to go through. It's a real shame because OpenAI used to write stellar documentation and publish really lucid papers just few years ago.
> they could have even used their own LLM to edit their documentation to fix grammar issues
In my experience companies who do this rarely stop at using LLMs to fix grammar issues. It becomes full on LLM speak quite fast, especially if there isn’t a native English speaker in the room who can discern what’s good and bad writing.