March 3, 2025. I look back at the past few years with a mix of nostalgia and awe. It feels like just yesterday when AI was still in its infancy, but now it’s everywhere—every platform, every tool, every workflow has an AI copilot or agent ready to help. As someone who’s been deeply involved in this shift, I can’t help but wonder what drove us all here.

Let’s talk about the tools that made it possible. The rise of eBPF (extended Berkeley Packet Filter) was a game-changer. It allowed us to write efficient and flexible programs directly into the kernel space without rebooting, making our ops teams more agile. Wasm + containers converging? Yes, they’re now indistinguishable from each other in most of my work. The lines between them are blurred, but that’s fine because it makes everything easier.

One of the biggest changes has been how we use AI in infrastructure. Back in 2019, the idea was still wild and controversial. Now, platform teams have fully embraced it—owning the entire lifecycle from data ingestion to model deployment. It’s become so seamless that developers rarely think about it anymore; they just expect their code to be automatically improved by an AI copilot.

But let’s talk tech. I remember when AIGC (AI-generated code) was hyped, but now it’s quietly integrated into our pipelines. The recent release of Mistral OCR is a great example—suddenly, scanning documents and extracting data has become incredibly fast and accurate. It’s hard to go back to the old ways.

One particular project I’m proud of involved shipping a new feature that leveraged these advancements. We were working on an application that needed real-time insights from complex data streams. Our solution used eBPF for low-latency processing, coupled with AI models running in Kubernetes clusters. It was a tight fit, but it worked perfectly.

Yet, as much as I love the efficiency and automation, there are moments when I feel like we’ve lost some control. The tools have become so smart that sometimes I wonder if they’re doing too much behind the scenes without my explicit consent. But then again, isn’t that what we wanted? Isn’t it better to spend time on higher-level problems instead of micro-managing every detail?

A recent event that hit home was when uBlock Origin got yanked from the Chrome Store. It made me realize how fragile our dependencies can be and how quickly things can change. In tech, nothing is permanent, not even something as widely used as a browser extension.

On another front, Apple’s restrictions on Pebble watches have been annoying but also somewhat amusing to watch. The contrast between the open-source community’s joy over new releases and Apple’s proprietary ecosystem highlights the ongoing battle between openness and control in technology.

All of these events—big and small—are part of this era. They shape how we work, think, and innovate. As I sit here reflecting, I can’t help but feel both humbled by our progress and a bit nostalgic for simpler times. But then again, maybe that’s the point—every new tool and technology brings with it both challenges and opportunities.

In the end, what matters most is how we adapt and evolve with this changing landscape. It’s an exciting time to be in tech, full of endless possibilities and constant learning. Here’s to the future—may it bring even more innovation and less hype.

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That’s where I stand today. The world has changed dramatically, but one thing remains certain: there will always be more to explore and overcome.