Title: When AI Became a Copilot

---

December 8, 2025. Today marks another milestone in my journey as an engineer who’s seen the tech world evolve over two decades. Reflecting on this year, I can’t help but think about how much the landscape has shifted, particularly with the rise of copilots and AI-assisted development.

Back in December 2014, when I first joined a platform team at my company, we were still grappling with Docker containers. The idea of eBPF was just a gleam in the eyes of a few researchers. Kubernetes was cutting its teeth, but it was far from the default. Fast forward to today, and container orchestration has become so mundane that it’s almost boring—yet essential.

This year, something significant happened: AI-native tooling became ubiquitous. Tools like Gemini Pro 3, which imagined what HN might look like a decade hence, have taken off. I’ve seen first-hand how these copilots have changed my day-to-day work. For instance, every time I write a script or set up a pipeline now, the language model suggests improvements and best practices almost seamlessly.

One of the biggest changes is in our platform team’s role. Historically, we focused on building robust infrastructures—firewalls, load balancers, storage systems. Now, we’re managing AI infrastructure pipelines, ensuring that the copilots we use are reliable and secure. This shift has brought both challenges and opportunities.

A recent incident highlighted these challenges. We were using an LLM-assisted ops tool to monitor our services when it suddenly started flagging false positives. The initial reaction was to disable the tool entirely, but then I realized that dismissing such tools would be a mistake. Instead, we spent time debugging the issues, finding that the model’s context was limited and it didn’t always understand the nuances of our system.

This experience taught us a valuable lesson: AI copilots are incredibly powerful, but they’re not perfect. We need to continuously monitor their outputs and ensure that human oversight remains critical. This balance is something we’re still wrestling with as an industry.

In addition to AI-assisted tools, the convergence of WebAssembly (Wasm) and containers continues to be a hot topic. While Wasm has been around for years, it’s only now starting to integrate deeply into our workflows. I recently worked on migrating some of our critical services to Wasm modules, and it was both exciting and challenging. The performance improvements were substantial, but managing the lifecycle of these new components required us to rethink our deployment strategies.

Multi-cloud has become the default for most organizations. While this offers more flexibility and resilience, it also means dealing with a myriad of cloud providers’ APIs and services. It’s no longer about just setting up infrastructure; it’s about orchestrating across multiple environments seamlessly. This year, we’ve been working on tools to abstract away some of these complexities, making multi-cloud deployment more manageable.

Reflecting on the past few years, I’m reminded of how quickly tech evolves. As someone who’s lived through many of these changes, I can appreciate both the progress and the challenges they bring. This year has been no exception—AI copilots are here to stay, and we need to adapt to this new reality.

In closing, let me share a personal anecdote that encapsulates the spirit of the era. I was working late one night when my Apple ID got locked out due to too many failed login attempts. Frustrated, I reached for a copilot tool, hoping it would guide me through the issue. To my surprise, it not only helped unlock my account but also suggested some best practices to avoid similar situations in the future.

As we move into 2026, let’s embrace these tools with both open arms and critical minds. We’re at a fascinating crossroads where AI is no longer a luxury but an essential part of our development and operations workflows. The future may be uncertain, but one thing is clear: change will continue to shape the tech landscape in ways we can only imagine.

Merry Christmas to all, and happy coding!

---

This blog post reflects on the rapid evolution of technology over recent years, highlighting key changes like AI copilots and Wasm while sharing personal experiences that underscore the need for ongoing adaptation.