271. Spiritual Home 中
The cover photo was taken over the weekend when I went to my spiritual home, Wang Xiaobo’s bookstore, and sat there for a whole morning, reading “A Maverick Pig” that I’ve read several times, and grabbed a cup of Silver Age coffee on the side, which was really nice. Big thanks to the friend who pointed out that the past few issues of the weekly were a bit shallow, I’d been too absorbed in AI Coding. I take the criticism, and from now on I’ll keep the content more interesting, and strive to make it a spiritual home for everyone.
Recording down-to-earth trending tech I see every week, filtered and published here. Follow this weekly newsletter to get update notifications
Trending Tools
claude-tap: a local proxy and trace viewer for AI coding agents
https://github.com/liaohch3/claude-tap
Launch your CLI through it, or have it listen to the local app transcript, and you can see the real API traffic and agent context: system prompt, conversation history, tool schemas, tool calls, streaming responses, token usage, and request diffs. Worth a try for anyone who wants to dig into how it works.
VidBee: a nice tool for downloading videos from all kinds of sites
https://github.com/nexmoe/VidBee
It uses yt-dlp as its underlying engine, so it can download videos from almost any site in the world, including YouTube, TikTok, Instagram, Twitter, and more. Give it a try if you need it, but mind the copyright.
Witr: helps you see why something is running
https://github.com/pranshuparmar/witr
When something is running on your system, whether it’s a process, a service, or something bound to a port, there’s always a reason. That reason is often indirect, non-obvious, or spread across several layers. Plenty of other tools can tell you what is running; this one does a great job of telling you “why it’s running”, which is pretty interesting.
Dinky: a file compression tool for Mac
https://dinkyfiles.com/
It’s quite nicely made, just drag your files in. It supports compressing images, videos, and PDF files, so give it a try if you need it.
Just Looking Around
Ranking of LLM cache hit rates
https://dirac.run/posts/cache-hit-rates-agents
Kind of interesting. One reason domestic models keep their high cost-performance, along with the careful penny-pinching of our engineers.
Meituan’s AIGC tech innovation and practice for poster generation
https://tech.meituan.com/2026/06/18/AIGC-poster.html
Meituan is actually quite meticulous about how they build things and takes the time to distill methodologies. That said, these days I lean more toward using a more powerful model to solve problems in less time.
A fairly interesting record
It started with an email I received from a Russian teenager, along with a record of our back-and-forth replies, anonymized and then AI-generated. Russia is having a rough time right now, with even international bank cards mostly cut off. I’ve always thought of my products as global, with no political factors, letting everyone enjoy a bit of the fun of engineer tools, which is honestly pretty neat.
Just Writing
Walking ahead, or being pushed along
Lately I’ve had a feeling: engineers who have already transformed into AI engineers, versus those in traditional roles at traditional big companies who haven’t yet realized they need to transform, give off a vibe like the software engineers at the dawn of the internet versus the engineers working in the China Mobile / Unicom / Telecom direction at the same time. It’s also a lot like the difference between people using smartphones and people using feature phones around 2011.
Before, it just felt like a difference in choices. Now it feels like a slowly-boiling-frog situation, and the water has actually gotten a bit scalding.
Engineers walking ahead of where technology is heading will have far more room to maneuver, while those being pushed along by the tech direction or the organization will have a rough time.
Looking back through some of my pretty shallow past sharing, I was fairly lucky that after 2019 I basically stopped wanting to be a traditional role-based engineer. Back then I wanted to be more of an engineer who solves all kinds of problems, not limited to the role itself, dabbling in design, product, frontend and backend, and ops, more about solving a product’s problems.
Looking back now, it’s a good thing I kept at it, otherwise reaching this stage would honestly be pretty rough.
Honestly, working that way back then wasn’t all that well-liked, it looked unfocused, and I could only rely on the things I did myself to slowly help the engineers around me grow. But at the time I really didn’t overthink it, I just felt that solving problems was way more interesting than guarding my own job, and that I could explore a ton of interesting things, without expecting immediate results, just letting things happen in their own time. I never imagined that, a few years later when AI arrived, it would become a small little moat for me in this wildly tug-of-war world.
The content of the articles below is pretty disconnected from the rapid development of the current AI era. You can treat them as relics from ancient times, then put yourself back in that era, which should be fairly interesting. You can even read them against the timeline of AI development, which happens to let you see some of my own thinking and changes on the technical side.
2019-11-25 Product and Open Source Sharing
2020-03-18 Interaction Design for Admin Dashboards
2022-07-01 How to Hunker Down and Get Stronger in a Tough Climate
2022-07-29 How to Be a Product Engineer?
2022-12-09 How Engineers Can Get Things Done Clearly
2023-10-25 The Dilemma and Breakthrough of Next-Gen Frontend
2024-01-12 My Open Source Growth Journey
2024-09-09 Talking About Future Tech Trends
2025-07-17 How Engineers Can Invest Better
2025-08-17 The Impact of AI Coding on Programmers
2025-12-22 The Breakthrough and Growth of Next-Gen Engineers
2026-03-30 Kill the Hand-Coding Programmer