How We’re Using LLMs at Hudson Cloud Systems

By Tom Nault, CEO, Hudson Cloud Systems

Right now, AI and large language models, LLMs like ChatGPT, Claude, Gemini, Grok, and others are being talked about just about everywhere. But when you ask people how they’re using them, most say they’re using them for searches or to edit documents. They’re not getting anywhere near the full capability of what these tools can do. New tools are arriving every day without exaggeration. I spend about 30 minutes every morning to see what’s new.

At Hudson Cloud Systems, we’ve been using LLMs for quite a while now. We use them for everything from helping write and review code to shaping how we think about the future of the company. Some days, it’s research. Other days, it’s helping validate an idea. I don’t use LLMs to write things for me, but I do use them to edit and help shape the context of what I’m working on. Most of us here use them in some form every day. I use them to validate some of my thinking.

Before I joined Hudson Cloud, I did a lot of this the old way. I’m big on research and data and checking my assumptions. I’d spend weeks researching new markets, digging into competitors, or pulling together information just to make basic planning decisions. Now that kind of work can often be done in a few hours, and usually with far better results. According to McKinsey, LLMs have the potential to automate up to 70 percent of the time spent on tasks like data analysis, report writing, and communication planning. That lines up with our experience.

That changes how we operate. It lets us grow without hiring as many people for lower-value tasks and instead bring on great talent where it counts most. In a recent survey, over 40 percent of companies reported using generative AI to reduce time spent on routine tasks. We’re seeing the same benefit here.

There’s always a fear that tools like this will take jobs, but I’ve never seen that happen in net terms. What happens instead is that work shifts. People who were doing something that gets automated usually move into something else, just like when the PC came out. Everyone said it would eliminate jobs, but it created whole new industries instead. The same thing happened with cell phones, and again with the internet. Every time there’s a major shift, the economy expands. It doesn’t shrink. The only people left behind are the ones who refuse to make the shift.

We’re already seeing this play out. AI lets us do more with fewer delays, and that’s a good thing. It means less time wasted and more time focused on product development, customer needs, and growth. Right now, we’re building out a new dashboard that uses LLMs in a supporting role. This is one thing our cloud platform can do that the old IT models can’t. We’re also looking ahead at how this technology will shape our customers’ expectations. A lot of them are still running on old on-prem systems, and we think our cloud platform is better suited for where things are heading, and we can prove it.

We’re not reacting to what’s happening in the industry as an afterthought. We’re thinking through how this technology fits into our future, how it helps us improve what we offer, and how it can give our customers something better. We’re out to adapt ahead of the latest AI and not just chase it. We’ve already been ahead of the curve in adopting LLMs, and that’s put us in a better position to grow, adapt, and build a product that makes more sense for what’s next. We think it’s an exciting time and we can’t wait to see what comes next.