How do you balance moving fast with protecting the trust that you've worked so hard to build so that it doesn't come out in dollars like you said before?

biggest thing that I see failures happen is when you don't have a repeatable process.

When you have a repeatable process, a proven process, you can automate it.

So the things that people want to see go fast and be consistent, you can automate.

And that leaves more time for the people that are doing the important part of building, maintaining, and reassuring the the relationship you've built with your client or your customer, and it leaves more of the...

When you have a process that is easy, refined, it looks like it's been done a million times, that builds confidence that you're... your customer, your client has chosen the right partner to solve.

No one ever wants to be the first patient on the table, right? That's just a fundamental.

And I think especially in the startup world where you spend a lot of time I wondered what you're seeing from startups that are using AI particularly well versus just adding something because investors or customers expect them to.

How does your company help people?

So the best way to think about it is over the last 30 years, I've worked with many startups.

I've worked in scale-ups.

I've worked in service providers.

And I've had the privilege of learning how those businesses work, how do you build and measure and deliver on success, especially in the managed services space when you get into the technology space.

And over time, I found that as we have changed technology, especially now with the adoption of AI in all of its iterations, it's almost harder for some companies to get back to the fundamentals of supporting your clients, understanding their needs and their desires, the basic fundamentals of business.

So what I did was a few years ago, I went and became an independent consultant.

How much do you think success depends on raising capital or getting injections of capital? And maybe that's totally dependent on the kind of company, but I mean, what are you seeing right now?

When you're talking with particularly industrial and manufacturing organizations, as far as bringing this new technology in, where do you think they are on that maturity curve today?

It's really interesting to me to see how wide that spectrum band is of AI adoption in our industry and where they're adopting it.

I'm seeing some older machine shops and manufacturers that still have very old equipment, and for them, for what they're doing, adopting AI closer to where they create the product doesn't make sense yet.

So what they're focusing on is how do we use AI around efficiencies of business processes, development processes, research, engineering, things that basically we can lighten the load or things that maybe are an after-the-fact item, like documentation, things of that nature.

They're leaning into that more.

Some of the more advanced are getting to the point where they're ingesting basically these datasets and are turning AI into a first point of contact for their technical users.

That at that point they can take the entire envelope of data around their product or service, and I'm seeing this especially with a really technology-focused, uh, manufacturing equipment, things of that nature.

For those that aren't, is there one misconception that stands out to you that, that, that might still be out there about AI that might be holding them back?

And

you're spot on.

I still do... quite a bit of fractional works, CIO, CISO, CTO, right? We've been in the industry a long time.

We can fill a lot of shoes.

And I recently had a case where it was a cheap revenue officer was doing things and the results came out great.

And then we kind of took the pieces under the hood back to the development team.

And I said, guys, this is a great start.

Where do you think we'll be?