Oct 5, 2026 · 1 hr 14 min · 18 segments
**Introduction** - Bill Hewitt's early career at Hyperion - The role of data in enterprise applications - Transition to contract lifecycle management **Interview** - Bill's journey to Linksquares…
Bill HewittGuest
Michael BernzweigHostLouis PinedoPanelist
Paul SoleilPanelist
And I have to say, I think we're at one of the most interesting times in technology that I can remember.

And I think part of that's being driven by just the speed of technological change.


I think the first question to ask is like, how do we use AI in the most productive way? So we're really moving from asking the question, you know, how do we reduce costs? How can every employee create more value? And, you know, what do I mean by that? Sort of like, if you think about Technology to date, it's really been about making humans more productive.

And now we're shifting with agentic to having systems actually do work on behalf of those humans.

Now, before everybody gets too crazy and says, we're going to replace all these jobs, the reality is any technology shift has the economic driving impact of creating even more jobs.

There'll be different types of jobs, more supervisory types of jobs, but more jobs nonetheless.

So when you think about why that is, first, it's really understanding the force multiplier that is AI.

So what does AI do? Well, first, it makes you far more productive as an individual.

For example, yesterday I was looking at a company and instead of reading eight quarterly board reports in a row, each board report about 80 pages.

And within a matter of minutes, I had a four-page summary on the trends, the issues, the challenges, and some insights that I hadn't really anticipated.


It allows everybody to have access to the same level of expertise that may be available through only one person before.

So another great example is at Link Squares, we've deployed something called Product Agent, and it allows anybody in the company to ask a question about how our product works.

And that query goes against a number of sources, but including our source code.

So it's not going against some stale knowledge base that's been maintained over the years by product marketing.

It's going against the actual code itself and telling you how the product works as of today.

And I have to say, I think we're at one of the most interesting times in technology that I can remember.

And I think part of that's being driven by just the speed of technological change.


I think the first question to ask is like, how do we use AI in the most productive way? So we're really moving from asking the question, you know, how do we reduce costs? How can every employee create more value? And, you know, what do I mean by that? Sort of like, if you think about Technology to date, it's really been about making humans more productive.

And now we're shifting with agentic to having systems actually do work on behalf of those humans.

Now, before everybody gets too crazy and says, we're going to replace all these jobs, the reality is any technology shift has the economic driving impact of creating even more jobs.

There'll be different types of jobs, more supervisory types of jobs, but more jobs nonetheless.

So when you think about why that is, first, it's really understanding the force multiplier that is AI.

So what does AI do? Well, first, it makes you far more productive as an individual.

For example, yesterday I was looking at a company and instead of reading eight quarterly board reports in a row, each board report about 80 pages.

And within a matter of minutes, I had a four-page summary on the trends, the issues, the challenges, and some insights that I hadn't really anticipated.


It allows everybody to have access to the same level of expertise that may be available through only one person before.

So another great example is at Link Squares, we've deployed something called Product Agent, and it allows anybody in the company to ask a question about how our product works.

And that query goes against a number of sources, but including our source code.

So it's not going against some stale knowledge base that's been maintained over the years by product marketing.

It's going against the actual code itself and telling you how the product works as of today.
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