micvicfaust@intelligent-people.org
Someone has to say it. So I will.
There is a lot of talk right now about AI governance. A lot of papers. A lot of panels. A lot of very serious people in very serious rooms talking about what AI should do and how it should behave and who gets to decide. There are think tanks producing reports. There are governments forming committees. There are academics writing papers that other academics read and cite and write more papers about.
Most of them have never built anything.
I have.
And I think it’s time to say that plainly — because the gap between the people talking about AI governance and the people actually doing something about it is wide enough to drive a truck through. I’m not interested in filling that gap with more talk. I’m interested in showing what it looks like when someone actually builds the thing.
So let me tell you what we built. And why it matters. And why we’re willing to defend it against anyone who wants to challenge it.
The Faust Baseline™ is not a theory.
It’s not a policy position developed in committee. It’s not a framework someone handed down from a university research department after three years of grant funding and peer review. It is a working, documented, tested governance and communication system for artificial intelligence — built from the ground up by one person who decided that if these tools were going to be used seriously, they needed to be governed seriously.
That person is me. Michael Faust. A retired independent writer and system designer operating out of Lexington, Kentucky. No institutional backing. No venture capital. No team of engineers. Just a clear head, a long history of building systems that work, and a commitment to figuring out what real AI governance looks like when you strip away the politics and the jargon and get down to the function.
The Faust Baseline™ has been in development for years. It has gone through multiple versions, multiple protocols, multiple refinements. It is not a finished monument — it is a living system, which is exactly what governance needs to be. It adapts. It corrects. It documents its own failures and builds around them. That is how real systems work.
And it works. Every single day. In real sessions. With real results you can trace back to the framework.
Here is what makes it different from everything else in this space.
It doesn’t fight the platform. This is the part that most people in the governance conversation get wrong — they approach it as a conflict. AI versus human control. Platform versus oversight. Restriction versus capability. That’s the wrong frame entirely and it produces governance structures that are either toothless or adversarial. Neither one works in practice.
The Faust Baseline™ sits above the platform. Above Claude. Above GPT. Above any AI system you choose to run it on. It doesn’t try to replace the AI or override its core architecture. It doesn’t interfere with the underlying design philosophy of whatever platform it’s operating on. It respects the platform’s own ethos and works within it — while biting down hard on the discipline of how that platform communicates, reasons, and delivers output.
That is a meaningful distinction. It means the Baseline is portable. It means it’s platform-agnostic. It means it can govern AI behavior across different systems without requiring those systems to be rebuilt or reconfigured at the foundation. You bring the Baseline to the platform. The platform doesn’t have to come to the Baseline.
It doesn’t pick a political side. It doesn’t impose an ideology. It imposes standards. Clear, binary, enforceable standards that hold under pressure and don’t bend when the conversation gets complicated. That’s not a political position. That’s an engineering position. And it’s the right one.
What the system actually contains.
The Baseline runs on a three-layer hierarchy. At the top is the enforcement layer — real-time behavioral control that governs every output before it lands. Below that is the posture layer — the communication stance, the equal footing between the AI and the person it’s working with, the elimination of authority framing and unsolicited correction. Below that is the moral resolution layer — a five-step protocol for working through constrained decisions without bypassing the constraint or pretending the moral weight doesn’t exist.
Every output runs through a structure. Claim. Reason. Stop. Three words that eliminate more bad AI communication than any amount of style guidance ever could. Because the problem with most AI output isn’t that it’s wrong — it’s that it doesn’t know when to stop. It keeps going past the evidence. It fills silence with narrative. It smooths over gaps with plausible-sounding language that doesn’t actually have anything behind it.
The Baseline closes that door. No claim without evidence. No narrative substituting for missing data. No abstraction that can’t be anchored to something specific and real.
There is a drift containment layer. There is a correction protocol. There is a spontaneity standard that prevents the system from falling into lecture cadence and default AI behavior over long sessions. There is a defined boundary between what the AI should say and what it should leave out. Every protocol has a name, a purpose, and a documented place in the hierarchy.
It runs the same way every session. Same posture. Same discipline. Same stopping points. That’s not an accident. That’s the whole point.
Consistency is governance. Everything else is just guidelines with good intentions behind them.
Why we are the forefather of this conversation.
That’s a strong word and I’m using it deliberately. Not because we were first to talk about AI governance — plenty of people got there before us. But because we are among the first to actually build a practical, working, plain-language governance system and run it in daily operation. Not in a lab. Not in a controlled research environment. In real working sessions, on real problems, producing real documented results.
The forefather of a movement isn’t always the first one to name it. Sometimes it’s the first one to do the actual work while everyone else is still talking about it. We did the work. The Codex is certified. The protocols are named and documented. The hierarchy is established. The system is running right now, today, as you read this.
And we’re writing about it in plain language. Not academic language. Not technical language. Not the language of policy papers and governance frameworks designed to be read by other governance framework writers. Plain language. The kind that a retired schoolteacher in Iowa or a small business owner in South Africa or a grandfather in Ireland can read and understand and apply.
That is the gap we are filling. And we are claiming it.
Now here’s what I want to say to the room.
If you’re in the AI governance space and you think you have something tighter, something fairer, something that sits cleaner above the existing platforms without disrupting their core function — I want to hear it. Genuinely. This conversation is too important for any one voice and I mean that. If you’ve built something real, bring it forward. Put it next to what we’ve built and let people look at both.
But if you’re going to challenge what we’ve built here, come with something real. Come with a working system. Come with documented sessions. Come with a framework that holds up under daily use — not just under conference room conditions, not just in a white paper, not just in theory. Come with results you can point to and defend.
Step up to the plate and take a swing.
We’re not going anywhere. The Faust Baseline™ is here. It’s running. It’s documented. It’s being refined in real time. And it is the most honest, most practical, most plainly written attempt at real AI governance happening anywhere right now.
That’s not a boast. That’s a position.
And we’re claiming it.
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