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Product Engineer - Michael Pidgeon

Building the AI engineering under the hood - from how Wordsmith reads and reasons over documents to the evals that keep it reliable.

Michael Pidgeon

Product Engineer

Getting closer to the work

I joined Wordsmith as a product engineer, although in practice the lines between product engineering and AI engineering blur quite a lot here. That was part of the appeal for me. I had worked with AI before, but more at a strategic level, thinking about how to get teams up to speed and how to help people use the technology well. At Wordsmith, I wanted to be more hands-on again.

That has been one of the best parts of the move. You are in the work every day, surrounded by people who really understand AI engineering, and that changes how quickly you learn. It is not just that people are smart, although they are; it is that everyone is experimenting, testing, trying new approaches, and then sharing what they are finding as the work develops.

I think the role of the software engineer is changing quite a lot, and I wanted to be closer to that change rather than watching it from a distance.

Why I joined Wordsmith

I knew a few people at Wordsmith before joining, and they had been speaking to me about it for a while. They were not just saying it was a good company; they were raving about the problems people were working on, the pace of the product, and the feeling that the team was right in the middle of where AI engineering was heading. What stood out was not just that the team seemed strong, but that people had good taste, high standards, and real curiosity about the work. 

They were thinking seriously about trade-offs, product quality, how far the tools could go, and where the fundamentals of engineering still mattered. The work sounded genuinely interesting too: problems that involve reading, understanding, comparing, validating, and reasoning across large volumes of information, in a space where AI can be useful, but only if the product is built carefully enough to be trusted.

Legal is a particularly interesting area for AI because so much of the work involves reading, understanding, comparing, validating, and reasoning across large volumes of information. But it is also an area where quality really matters. You cannot just move quickly and hope for the best. The product has to be reliable, because people are using it for serious work.

That is one of the things I like about building here. You are working quickly, but you are also having to think properly about testing, quality, architecture, and how the system behaves in the real world. Some of the fundamentals of software engineering have not gone away just because the tools have changed. If anything, they matter more.

A culture of experimentation

There is a real culture of experimentation at Wordsmith. If you have an idea, you are encouraged to try it, but it is not just based on gut feel. We use evals, testing, and real evidence to understand whether something has improved or not. That gives you the confidence to make changes, because you are not just guessing.

The way we work can change very quickly. Something that was not possible three months ago might now be possible, and that means you have to stay flexible. You are not usually sitting on a neatly defined three-month project where everything is mapped out from the start. The goals can move, the tools can change, and the best approach might not be obvious until you have tried a few things.

That kind of environment is not for everyone, but if you like solving problems in new ways, it is a fun place to be. There is not a huge amount of process, and there are not too many meetings. The philosophy is more like: hire smart people, set a high bar, and let them get on with it.

"Honestly, I think legal is the next big thing after coding, and I wanted to be building it hands-on, with people who genuinely know what they're doing, on a product I actually believe in."

Feeling the impact of what you build

One of the things I value most is that the work feels like it matters. The engineering team is still small enough that your contribution has a visible impact, and when you improve a part of the product, you can feel the difference it makes.

There is also a strong in-person culture, which I really like. The energy of the place was one of the things that stood out to me when I was applying. People are genuinely fired up about what they are building, and there is a curiosity about the technology that comes through in the day-to-day work.

What you get from Wordsmith is a very serious education in how AI-native software is being built. You learn from people who are thinking deeply about the craft, but you also learn by doing, by making decisions, by testing ideas, and by seeing what works. I think that puts you in a very good position, whether you want to keep building inside a company like this or eventually build something of your own.

For me, it feels like a place where the work is interesting, the product is strong, and the people around you make you better. That combination is hard to find.

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Copyright © 2026 Wordsmith AI. All rights reserved. WORDSMITH is a registered trade mark of Wordsmith Law LLP and is used under licence.

Copyright © 2026 Wordsmith AI. All rights reserved. WORDSMITH is a registered trade mark of Wordsmith Law LLP and is used under licence.