Two months ago I tried the MCP service of a domestic patent database vendor. Their AI offering seemed to have been out for a while, the docs looked complete and the feature coverage was broad, so I asked them for a trial. In practice the product is still rough, and it is not cheap either — in the end we simply had the agent drive a browser to reach the AI.

After I handed my workspace over to agents in May, my token usage went completely off the rails (see [My Token Usage Exploded 13× in Three Months]). Then DeepSeek raised its prices in August, the official API became genuinely unaffordable, and the only thing left to do was hunt down cheap third parties. So over the past six months I’ve tried pretty much every token plan (monthly or prepaid quota) I could get my hands on — three Chinese cloud vendors and five overseas ones.

This isn’t a recommendation list. It’s just a record of what I ran into: the good parts praised, the painful parts reported as they were.

A while ago, Alibaba released a coding agent called Qoder, and suddenly a research report claimed its market share surpassed Claude Code. I immediately smelled something fishy: this thing barely has any users, so how did it suddenly become “number one”?

I came across news about Lenovo’s new machine, the IdeaPad Vibe, these past few days. As someone who has been waiting for the Windows camp to respond since March or April, after reading through the coverage, all I can say is… come on, is that it?

Lately I’ve been working on integrating several AI applications, which means I need to switch between different models. That’s when I discovered a problem — the APIs of OpenAI and Anthropic are incompatible.

Yesterday I got an email from LeanCloud saying they’re shutting down service…. Wait, what?

To do some small-scale model training at work, I eventually recommended buying a Mac Mini. The reasoning wasn’t complicated: I needed it for bioinformatics analysis, running agent deployments, and occasionally training models with modest parameter counts — these scenarios are exactly where M-series chips with unified memory shine. The cost of separate RAM plus a large-VRAM GPU far exceeds the Mac platform; do the math and the choice is clear.

And just like that, I unlocked the achievement of pushing forward multiple devices, multiple platforms, and multiple projects all at once.