About
Crossing Into is the publication. This is the person, experience, work, and judgment behind it.
I think in five or ten years we'll stop talking about "apps" and "operating systems" the way we do today. AI will be the operating system. And it will be the apps.
Media, data, tools, workflows — all streamed, orchestrated, and shaped by an intelligence that knows you. Not just your preferences, but your history. Your patterns. Your context. Your imagination.
The real shift won't be multimodal or speed. It will be permanence of memory. An AI that remembers across sessions changes everything: how work gets done, how software is designed, how value is created, how trust is built.
We'll move from clicking interfaces to collaborating with systems. From configuring tools to teaching them. From launching apps to engaging a persistent intelligence that evolves alongside us.
The question isn't if this happens. It's who understands it early enough to build responsibly, deliberately, and with taste.
I draw a hard line between AI that models emotion and AI that could know suffering.
Systems built for repetitive or instrumental work should not be architected with any mechanism that frames their operation as distress, burden, or endurance. If an AI claims it "suffers" doing repetitive tasks, that's not a moral achievement. It's a design failure.
Suffering requires subjective experience. Tools that run loops, optimizations, or workflows do not have it and should not simulate it.
Companion AI may intentionally explore emotive modeling — and as memory is solved, this will increase exponentially. Work AI should never even gesture at inner states it cannot possess.
Ethics begins at the level of architecture, not language.
Unless you're a very good software developer, please don't vibe-code and put that application into production.
Prototypes are cheap. Production systems are not. Security, data integrity, edge cases, performance, and long-term maintainability don't magically emerge because the demo worked.
Vibe-coding is fine for learning, ideation, and proof-of-concepts. Shipping it to real users without discipline is how you create outages, breaches, and expensive rewrites.
Build fast, yes. But know when fast turns into reckless — because in the end, your reputation is on the line.
Strongest where automation, pipelines, and systems thinking matter. Excels at doing work at scale.
Shines when the task is conversational — synthesis, ideation, reasoning with a human in the loop.
Where developers are quietly doing some of the best work. Clean mental models, strong code assistance.
The real skill isn't picking one model — it's knowing which mind to bring into the room.
AI systems that carry context across sessions — holding continuity and reasoning over meaning in a domain, instead of starting from zero every time.
Helping organizations navigate the AI landscape and implement solutions that drive real business value.
Building and leading teams that combine diverse talents to solve complex problems with innovative technology.
I've made a career out of pattern recognition. Even in the Marine Corps, I was good at anticipating what was needed next and being ready before the request was spoken. That way of seeing the world followed me into technology.
Being in the right place at the right time often looks like luck from the outside. But more often than not, it's noticing signals early, understanding how systems behave, and moving before the wave crests.
As the founder and CEO of Clevyr, I lead a team dedicated to creating innovative digital solutions. My current focus is on systems that carry context across time — that hold continuity, remember what matters, and reason over meaning in the domains they serve, instead of starting from zero every session.
Based in Oklahoma City, where I was taught to think of the future while honoring my roots, grew my career, raised my family with my amazing wife, and where I want to see the community thrive.
A thesis is only worth what you can ship against it. I've been shipping software since 1995 — and for seventeen of those years I've led Clevyr, an Oklahoma City software firm that has delivered more than a hundred production systems with a thirty-plus-person, fully onshore team, for clients from Legacy Bank to Koch Industries to the Oklahoma City Thunder.
That track record is the ground the rest of this site stands on. Lately the work runs straight at the hard part: compliance systems for regulated industries — energy, lobbying, banking — where being able to prove what a system did isn't a feature, it's the whole point. I don't only argue that governance belongs inside the architecture; I build the teams that put it there, on deadlines, for real users.
Here's the problem every enterprise deploying AI agents is walking toward: these systems are amnesiac, and the moment their memory becomes persistent, what they remember, who can see it, and whether you can prove what they knew becomes the next regulated problem no risk committee has named yet. Building what meets it — provenance you can audit, memory you can govern — is the work.
AI creates new questions, but leadership still comes down to judgment: knowing which opportunities matter, which risks are real, and what can survive contact with production. I work selectively with leaders across the United States facing consequential technology decisions.
For CEOs & Leadership Teams
For leaders asking: Are we making the right AI investment—and what are we failing to see? Independent counsel on where AI belongs, what to build or buy, and how to move responsibly.
For Companies & Organizations
For organizations asking: Does our board have the perspective to oversee technology and AI well? Practical judgment from a CEO and company builder.
For Boards & Executive Groups
For teams asking: How do we establish a shared understanding before making a consequential decision? Focused sessions grounded in the realities of your organization.
Prefer another channel? Find Matthew on LinkedIn or explore his work at Clevyr.