Navina Lang

I enjoy building software where engineering, product and business come together.

My background started in financial systems through Web3, where I spent 3.5 years as the founding protocol engineer at Velvet.Capital. Building production financial infrastructure taught me to think carefully about security, correctness and long-term maintainability. When software is responsible for real assets, small mistakes can have expensive consequences, so good architecture isn't optional.

Those lessons still influence how I build software today, even though my focus has expanded beyond Web3.

Engineering is changing

Over the last few years I've realised that software engineering is becoming less about writing every line of code and more about making good decisions.

AI has changed how software is built. I use it every day because it allows me to build faster and explore new technologies much more quickly than before. But I don't see AI as replacing engineering judgement. If anything, it makes good judgement even more valuable.

The questions I find myself asking are rarely about syntax anymore.

• What problem are we actually solving?
• Which parts of the system need to remain flexible?
• Which decisions should be permanent?
• Where should AI help, and where do we still need deterministic behaviour?
• How do we keep today's solution simple without making tomorrow harder?

Those questions usually matter far more than the programming language.

How I like to build

I enjoy taking an idea from a blank page to a working product.

That means thinking about architecture, user experience, workflows and long-term maintainability before getting lost in implementation details.

I'm naturally curious and enjoy challenging assumptions. If something feels overly complicated, my first instinct is usually to ask whether there's a simpler approach. At the same time, I like thinking ahead about how a product might evolve as requirements change, rather than only solving today's problem.

Recently I've been building AI-native applications like PolicyFlow, an AI-assisted contract review platform, and an Expense Tracker focused on modern SaaS architecture. These projects are opportunities to learn new technologies, experiment with different design decisions and continue improving as an engineer.

Looking ahead

Financial systems remain one of my biggest interests, especially where AI, enterprise software and digital assets intersect. I'm also increasingly interested in Real World Assets (RWA), where many of the architectural challenges I worked on in Web3 apply just as well to traditional finance.

More broadly, I enjoy building products that solve real business problems. Technologies will continue to change, but good engineering decisions, thoughtful architecture and understanding the people using the software remain constant.

That's the direction I'm continuing to invest in.