Looking back, I learned to use FrontPage to create web pages since elementary school, but except for GitHub Pages, I never really set up and operated my own website. However, now it’s possible. With the support of agents and SaaS services, creating and launching a website has become quite simple…

I’ve been trying to use AI Agents / workflows to build efficient agent teams or AI workflows to improve productivity. After two weeks of experimentation, I’ve encountered several pitfalls…

Last year, I explored AI topics purely out of personal interest. This time, it’s under pressure from my boss… Even though I’m full of resentment, I still need to write something down to accumulate experience…

git worktree is a powerful feature provided by Git that allows you to check out multiple branches in the same repository simultaneously. Like cherry-pick, I hadn’t heard of this feature before, but in today’s era of extensive AI Agent applications, this feature will likely become as fundamental and essential as commit.

The Lunar New Year holiday is supposed to be a time for lying back, watching videos, and playing games. However, as a dedicated workhorse programmer, how could I possibly let myself stay idle? So, during the break, I tinkered with opencode + MiniMax/Deepseek and came up with a few little things (definitely not because I got utterly wrecked in Street Fighter on New Year’s Eve and needed a distraction).

Previously, I had tried modifying and adding recipes to conda channels. This time, I want to package my DevSSH and upload it to my own channel. I decided to try building a conda package myself.

I wanted to contribute to the Fydetab Duo Wiki, but to preview the blog locally, I needed to add pixi or other configurations to the project. These changes were not suitable for the original repository. So I learned how to selectively submit commits, which is where git cherry-pick comes in.

The new year has brought another AI surprise…

Preparing a resume may not sound difficult, but in practice, it can be quite time-consuming. Nowadays, many jobs have specific requirements for niche knowledge or projects. With so many job seekers, a resume that doesn’t highlight the key points relevant to the job requirements might be overlooked by employers. Therefore, to achieve better results, it’s best to tailor your resume for each position… This is something AI should be good at, but at least for now, I haven’t found a good free tool for this.

Recently, I came across RenderCV, a tool that generates resumes from YAML configuration files. It enables a “configuration-as-resume” approach. Combining it with an AI coding assistant like Aider essentially creates a rapid resume preparation environment.

Last year, when I joined my current company, I was tasked with preparing a teaching analysis environment for bioinformatics training. This opportunity introduced me to Pixi. Later, as my responsibilities shifted, I not only continued with bioinformatics analysis but also took on full‑stack maintenance work. The projects I handled spanned front‑end and back‑end, involving languages and frameworks beyond the data‑science staples R and Python. Pixi has still been able to serve as a cross‑language/stack development environment management tool (Conda offers an extremely rich resource pool, covering mainstream programming languages and common frameworks). Therefore, I’d like to summarize the practical Pixi features that have proven useful in my daily work.