Title: When AI Became My Co-Pilot: A Year in Engineering

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January 26, 2026. It feels like just yesterday that AI was still the shiny new toy, but now it’s everywhere—my co-pilot, my sidekick, whispering suggestions and corrections as I navigate through complex systems. This year has been a whirlwind of change, with platform teams owning AI infra pipelines, eBPF making its mark in production, and WebAssembly (Wasm) and containers converging like oil and water.

The Early Morning Blues

Today started like any other: I got up, brewed my coffee, and checked my laptop. My morning routine is now punctuated by a few new steps—running AI-assisted debugging tools, checking LLM recommendations for the day’s tasks, and ensuring that my copilot sidekick is tuned to my preferences.

I fired up my editor and noticed a new plugin: “AI Copilot 2026.” It’s been a few years since it first appeared, but I’ve grown used to its presence. Today, as usual, it suggested some refactorings for the codebase. I accepted one of them, a minor change to improve performance that I hadn’t thought about myself.

The Kubernetes Conundrum

Later in the day, we had a team meeting. We’ve been moving towards more multi-cloud strategies, and everyone was discussing how our Kubernetes clusters were performing across different clouds. Kubernetes is now so ubiquitous that it’s boring—essential infrastructure rather than the bleeding-edge technology it once was. But that doesn’t make managing it any less of a challenge.

One of my colleagues brought up an interesting point: “We should consider using managed Kubernetes services more often.” I nodded, agreeing with him. Managed K8s has its benefits; it abstracts away much of the operational overhead and allows us to focus on application development rather than cluster management. However, there’s a catch—our internal security policies require us to maintain full control over our clusters.

I argued that we could strike a balance by using managed services where feasible but keeping critical applications in self-managed clusters for compliance reasons. The team seemed to agree, and I drafted a proposal outlining how we could gradually transition some workloads while maintaining the necessary controls.

Debugging with eBPF

In the afternoon, one of our production systems started exhibiting strange behavior. The logs were sparse, but I had an idea—eBPF. This technology has been around for a while now and is gaining traction in real-world applications. I decided to attach a BPF tracepoint to the suspicious process and watch what happened.

As I set up the eBPF program, I couldn’t help but think how far we’ve come since the early days of eBPF. Back when it was still experimental, debugging complex systems with it felt like pulling teeth. Now, thanks to improved tooling and support from Kubernetes, it’s become a standard part of our diagnostic arsenal.

Within minutes, I had isolated the issue—a race condition in one of our microservices that was causing unexpected behavior under heavy load. With this information, we were able to update the code and push out a fix before anyone noticed any issues.

The Tao of macOS Tahoe

Later on, while trying to resize a window on my Mac (Tahoe, as it’s called), I found myself wishing for simpler times. Resizing windows used to be a straightforward task, but now every system seems to have its quirks. It’s funny how tech that once seemed so revolutionary can become part of the mundane.

I chuckled to myself, realizing that even in this era dominated by AI and advanced infrastructure tools, there are still basic tasks that require human intervention. Maybe it’s time for a break from my desk—perhaps I’ll go take a walk around the office and enjoy some fresh air, letting my mind wander free from the constraints of code reviews and production issues.

Wrapping Up

As 2026 comes to a close, I find myself reflecting on how much has changed since the beginning of the year. AI is no longer just an exciting concept; it’s part of our daily lives in both personal and professional spheres. We’ve embraced tools like eBPF and Wasm, which have become essential parts of modern infrastructure.

Looking back at my career, I realize that while technology continues to evolve rapidly, the core principles remain the same: problem-solving, collaboration, and continuous learning. This year has been a mix of challenges and successes, all of which have shaped me as an engineer and a leader.

And so, as we enter 2027, I’m excited to see what new adventures await us in the world of tech—and perhaps some new tools that will make resizing windows on macOS Tahoe a bit easier.