AI safety checks should be fast, consistent and affordable.

PROME’s Care Core uses mathematical rules to keep core values, such as protecting life, separate from the AI that understands language.

In our latest internal comparison, Care Core and OpenAI’s GPT-6 Astra both made all 288 expected decisions correctly, across scenarios involving fake authority, coordinated pressure, tiny-risk loopholes and changing facts.

What do you do when teams of both human and AI agent swarm bad actors attack your system at scale?

And what’s the biggest problem with LLMs?

It’s their lack of reliability and inconsistency.

So, the planet resorts to guardrails and harnesses wrapped around the outside hoping it maintains brand guidelines, appropriate security and permissions, and doesn’t go off the rails.

There’s been much ado in the tech industry about OpenAI’s agents escaping its environments and hacking into its own and third-party systems like Hugging Face.

Seems like we gave toddlers keys to industrial equipment and let them go to town like they’re watching Bluey.

Per usual, we did something about it.

By the nature of the work we do, we see inside a lot of enterprise software companies and the products they build. Most of the time, boards and management teams are focused on differentiation of features, especially as it relates to AI these days. It’s a race to sameness. Everyone tracks everyone, so you’re forced to zoom in pretty deep to find differentiators.

There was a survey out last week that showed AI is less popular than nuclear waste. Ya got that? Nuclear waste. So now, when people ask me what I do, I say I build something worse for humanity than nuclear waste.

Actually, I don’t, and I’ll tell you why.

Over the last 3 to 4 years, as AI has proliferated throughout the economy and business world, the demand for us to help companies build internal products for only their use has increased substantially.

In the past, companies wanted to build external products and sell them to customers, which is what drove the wave of Enterprise Software as a Service (SaaS) companies. Now every company pays 10 to 30 software vendors to provide solutions for specific problems.

Shall we augment our reality?

Most of the technology industry thinks in terms of technology. It’s so ingrained in the way of being, that it’s hard to step out of it and imagine that technology isn’t always the answer.

Let’s take augmented reality glasses as an example.

Technology was never the moat. The product you built with it, and ultimately the experience you delivered from it, was.

We don’t share 99% of the decades of work for the biggest brands on the planet. Why? Because strong core values.

But, we would be remiss if we didn’t show evidence of what we mean.

What’s the state of middle market enterprise software, AI, and capital markets as we look out to the last 5 months of 2026?

Let’s get into it.

Financial markets are tricky little muses. They draw you in with the promise of a golden ring to rule them all, then prove to you over and over again you are not, in fact, smarter than the average bear.

Many moons ago in a galaxy far, far away I advised the Boards of the Fortune 1000 on metrics, goal setting, and incentive compensation design.

Said more plainly, we determined how much money you were going to earn based on how well you improved your business.

We live in interesting times. Since 1994, our planetary population has experienced the largest scale J Curve in human history.

VCs like to swing for the fences, so they strike out a lot. PEs prefer singles and doubles since they’re less risky. But they’re both missing something important.

Systemizing high-growth by consistently hitting triples. Very few can do it.

We’ve yet to see people using this exact phrase, but it represents the core need of enterprise software companies and their investors.

They simultaneously want profitable growth (i.e., driving EBITDA), but also AI Defensibility.

The way you maintain defensibility from frontier AI is, as you might have suspected, to build frontier AI. If you just use someone else’s, and get locked in, by definition your business operates at the whims of the Emperor.

I grew up in a small town in Iowa. In fact, I spent half my life there. What a magical place to grow up playing baseball. The second half of my life was spent living and working in the biggest cities on the planet: Chicago, New York, LA, Dallas, Nashville, London, Paris, Milan, Tokyo, the list goes on.

In short, I put in the time and did the research. The truth about what I found may surprise you.

The only real way you fail is if you stop.

Keep movin’.

We see many people make the same mistake on the road to creating product.

We’ll hear things like “People will love this”. And so we see a lot of market research, and surveys, and customer advisory boards take over. Sure, this will help you get part of the way there, but not all the way.

Inside Silicon Valley, you hear terms like “AGI-pilled”, which means you drink the kool-aid, you’re on the frontier, and you understand what’s coming with Recursive Self-Improvement (e.g., automate the automation).

But outside Silicon Valley, the feeling is different. Fear, Terminator, Job Loss, Apocalypse. It’s not great. And with the next presidential and political elections right around the corner, it means campaigning for popularity is about to begin.

The U.S. AI labs on the frontier used a three-fold pricing ladder as a business model:

1. Free to get you started

2. Subscription to get you retained (once you reach the free limit)

3. Usage to get you paying (once you reach the subscription limit)

Over the last 6 months, product development within enterprise software changed. We transitioned from 0% of new code written by AI to nearly 100%. And more recently, every company’s board and management team we work with is already there.