About us

Rob Nash

I’m a seasoned software engineer. My work has spanned startups, corporations, agencies, and my own projects, across finance, retail, healthcare, social media, field service, property, and aviation.

I’ve worked through several shifts in how software gets built. The one happening now is different. This time, the tools can write the code.

What that means for a working engineer is still unsettled. The loudest voices are certain in both directions, the job market hasn’t decided, and I’d rather not wait to be told where I fit. So I’m finding out for myself, the only way I trust. I build real products with AI, ship them, and keep them running in the open, so that whatever I conclude is something I’ve proven, not something I’ve read.

I can take risks a business can’t. With clients and revenue to protect, handing the work to AI is a gamble most can’t take. I can. If an experiment fails, nobody is harmed, I’m out nothing but my own time, and I’ve still learned something a company would rather not learn the expensive way. The freedom to be wrong is what makes the findings worth reading.

Audient is the clearest proof so far. The macOS app was built with AI, and it runs AI on-device, including Apple’s own models. The work spans the full range of Apple platforms, from iPhone and iPad to Mac, Apple TV, and Apple Watch, with open source libraries I’ll release along the way.

Here’s the first thing I’ve found, and it surprised me. The bottleneck was never the typing, and it turned out not to be the reviewing either. I don’t read every line any more. I built a system to do that instead, called Ordova: agents that review the code, enforce the conventions, check the copy, and watch for drift. My job moved up a level, from doing the work to building the system that does it, and then deciding whether to trust what it produces. That decision is still mine. It’s the part that doesn’t automate.

I’ve proven this works for me. Applying it in the field, where the stakes are higher, is a harder question. It means depending entirely on an AI agent that’s billed by the token, and that cost is trending up. No CFO would sign off on that today. It becomes viable the day the same models run locally, just as well, at zero token cost. In my opinion that day is coming, and before the end of 2026.