I recently worked on a small project: putting the Linux version of Claude Science into a Docker container, paired with an API Bridge so it can run through third-party API backends without needing to hold an Anthropic API Key directly.

The process was more eventful than expected—also quite interesting. Here’s a record of 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.

Recently, I chatted with friends about the devices we each want to buy, and we all shared the same feeling — everything is getting more expensive. Game consoles, graphics cards, RAM, SSDs, even laptops that used to be relatively affordable — the prices now are enough to make anyone hesitate.

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

I had been thinking that when my blog’s total page views hit 50,000 again, I’d write a celebratory post. Little did I expect that the clicks would grow much faster than I imagined — before I could even finish drafting the celebration, the number had already blown past it.

I’ve been living at MoFang Apartment for almost three years. What I got wasn’t a renewal notice — it was news that the company’s funding chain had snapped and they were on the verge of bankruptcy.

I recently got a Mac Mini to use as a server. I initially thought that since macOS is based on Unix, it would be pretty much like Linux — just set it up and go. But once I actually started using it, I ran into quite a few pitfalls. Here’s a record of the main issues.

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.

Recently I submitted a PR to BananaSlice (#11), adding configurable Gemini-compatible API endpoint support. The whole process made me realize: AI Agents not only help people write code faster, but also change how we leverage open source software.

Following up on the previous post [From Fydetab Duo to HP Chromebook X11], I have been using the HP Chromebook X11 for a while. The overall experience is quite good, but I encountered two annoying bugs. Here I record the solutions.