Becoming a technological investor or a user of technology is the easiest way for us to benefit from the AI era.

Recently, I’ve been thinking 🤔. In the current economic landscape, AI is the only growth point, and going with the flow might be easier. So, how can I find my place in this era?

My thought is that AI is a universal technology, just like electricity, computers, and operating systems. Not everyone needs to work in these foundational services, but rather find a position in the ecosystem built on top of them.

Wu Jun once said that, in the future smart era, only about 2% of the population will truly benefit from technological advancements, and these three types of people will enjoy the benefits brought by technology:

1. Those who own core technology
2. Those who invest in core technology
3. Those who apply technology

No tutorials or books needed, master a new language in 1 day (not for 99, not for 9.9, just if you’re willing to use it – classic sales pitch). This isn’t a dream, and it’s not an ad! AI models make learning a new language in no time possible.

Of course, this statement is a bit exaggerated. What I mean is that in the AI era, we no longer need to learn a new language the traditional way—learning first and then practicing. Instead, we can learn directly through practice.

This is my reflection after using Cursor for one month to learn front-end development.

Wake up, AI programming is not as simple as you think. Don’t blindly trust AI-generated code, current AI programming is not as good as you imagine.

I am a frontend novice. I spent 20 hours using Cursor to do secondary development on an open-source website project. After a flurry of activity, I found that none of the features were working anymore. And this open-source project was just a simple webpage website program.

This was my first time using Cursor as a novice. I had previously only used it as an auxiliary tool. My blog’s video playback page was written using V0 dev, the interface was refined using Kimi, and the video list page was written with Cursor.

While research CNI recently, I recalled an interesting issue I encountered during the development of network plugins and investigation of Calico: Calico assigns IP addresses to its own components’ Pods (e.g., calico-kube-controllers). How does Calico achieve this? From the installation of the Calico network plugin to assigning IPs to its own Pods, what happens at the underlying level?

This essentially poses a “chicken-and-egg” problem: running a Pod requires the CNI plugin, while the CNI plugin’s operation depends on the proper functioning of other Pods.

In today’s job market, freelancing is becoming increasingly popular and has become a choice for many. Recently, a friend of mine organized an end-of-year gathering for freelancers in Shanghai, where participants shared their career experiences and insights. Within an hour of the event announcement, the registration exceeded expectations and quickly filled up, highlighting the growing popularity of freelancing.

I have been a freelancer for 135 days now, and today I’d like to share some of my thoughts and methods during this journey.

On December 11, 2024, OpenAI experienced a major outage caused by a failure in the Kubernetes cluster control plane. For outsiders, this may simply seem like an interesting incident, but as an insider, I analyzed this failure from a technical perspective.

After reviewing the incident report, I came up with three questions:

• What is the Telemetry service used for?
• What are the “expensive requests” mentioned in the report? Why would this program generate a high volume of resource-sensitive API requests?
• Why did it impact the business systems?