Foxbox in the AI Era

Evolving with intention in the age of AI-amplified engineering

A year ago, most engineering teams were still treating AI like a novelty. Something to explore on the side, not something you’d bet the business on. Most agencies were still keeping AI tools at an arm’s length, including Foxbox.

I made a video not long ago about “vibe coding” and generally concluded that it yielded surprisingly quality results, but was still most applicable to proof of concepts or easily automated tasks.

When updated models of tools like Claude Opus, Gemini and Cursor were released earlier this year, the agency world reached a threshold. I firmly believe we’re now on the other side of it.

So we’re adapting. This article outlines what we’re doing now, what we’re learning in real time, and how we’re choosing to move forward as a company. It’s not a set of final answers. It’s a snapshot of how we think, how we build, and how we’re staying grounded while everything around us moves quickly.

Harnessing superpowers

AI now sits at the center of our development process, not at the edge of it.

Dependency upgrades, typically long and arduous processes, can now be completed in a fraction of the time. Which helps eliminate typical bottlenecks to innovation and new feature development.

We’re using Claude Code as a pair programmer working alongside our engineers to build new features. We lead the tool, breaking down the problem for Claude as if we were to write it ourselves. Claude writes the first pass of the code. Then we edit, review, and commit. Look out for security and performance issues. Collaborate with the tool to write unit tests. Claude Code opens pull requests and automates the arduous pull request description writing.

Here’s the key thing: our engineers are accountable and responsible for every line of code shipped. The tool helps, but we’re accountable.

When building front end functionality, we instruct Claude Code on exactly what we want it to look like by providing screenshots of Figma or example code. It does a very good job. Then we use our expertise to fine tune and get the UI just right.

We’re using tools like Claude Code and Cursor to dramatically speed up bug fixing. Instead of manually writing failing tests and debugging step by step, we feed the bug into the AI, which helps generate a test case, suggest a fix, and even write the pull request. This automates much of the traditional TDD workflow and helps us resolve issues faster and with more confidence.
These aren’t shortcuts.

They’re scaffolding that helps our engineers move faster without cutting corners.
Of course, we don’t just hit “accept” on AI output and ship it. Human oversight is built into every step. In many ways, these tools haven’t made software easier to build, they’ve made it more possible to build exceptional software in far less time.

Speed Is easy. Thoughtfulness isn’t.

We’ve seen the critiques. That AI-assisted code erodes discipline. That it nudges teams toward shipping faster instead of thinking deeper. That it risks turning engineers into editors. And some of those concerns are valid.
But the solution isn’t to slow down out of fear. It’s to build systems of accountability and lean into the process.

We’re not handing off thinking to machines. We’re extending our own capacity to think with quicker clarity and greater context. When we automate a test suite or use AI to surface a cleaner refactor, it’s not because we’re lazy. It’s because we want our engineers focused on what only humans can do: make tradeoffs, understand users and build systems that adapt .

Evolving the craft

I’m proud that I have a development and engineering team full of people that take tremendous pride in their craft. As an engineer who had to work hard to let go of writing code, I understand the defensive instinct or hesitation lots of engineers are feeling right now.

The craft of software engineering isn’t about elegant code for its own sake. It’s about solving real problems through thoughtful systems. Great engineering bridges the gap between what a product does and what people actually need. The best solutions are often invisible—seamless, intuitive, and built with care.

That’s the work that matters most.

It’s about solving problems. Bridging gaps between product and user. It’s invisible architecture and elegant functionality, using the most advanced tools at our disposal to build things that impact people’s lives. It’s about the insight, creativity and attention to detail that makes a product so seamless and intuitive that it becomes indispensable.

That’s the craft. Engineers that learn to be less precious about their code will be the first to remaster it.

We're still writing the rules

We’re choosing to ride the wave of change: document as we go, evolve with intention, and stay focused on maximizing value to our clients. That tracks with what we’re seeing. The developers on our team aren’t just getting more done.

They’re spending more of their time doing higher-value work.
So what does it mean when all engineers become leads? What blind spots might future engineers have if they never actually learn the basics of programming?

Nobody knows exactly what’s next. That’s the point.
We’re not trying to predict the endpoint. We’re designing for the middle. For the messy, fast-changing space where smart humans and fast machines solve problems together.

If we’ve learned anything over the past year, it’s that you can’t wait for certainty to take action.
So that’s what we’re doing. We’re not claiming to have it all figured out. But we’re moving fast, thinking deeply, and having the conversation out loud along the way.

Let’s keep building.

Rob