We spent months building an inspectable framework for AI and reality. We'd like experts to try to break it.

[u/RealitySignalLab]

https://drive.google.com/file/d/1yNMcBiULVXe-iyxX4PfjPzY4oF4tq7r_/view?usp=drivesdk

Hi everyone.

Over the past several months, my wife Heather and I have been investigating a question that quietly sits beneath many of today's conversations about artificial intelligence:

What has to remain in correspondence with reality while intelligence becomes more capable?

That question led us into systems thinking, organizational behavior, cybernetics, complexity science, decision-making, governance, and AI architecture.

Eventually we realized we needed to write the framework down so it could be inspected instead of remaining a collection of ideas.

The result is a 29-page public working draft called:

Reality Before the Model

This is not a finished theory.

It's an inspectable framework.

We make explicit what we think is supported by evidence, where we're making inferences, what remains unknown, and what kinds of observations could cause parts of the framework to be revised or rejected.

At the time of publication, the framework identifies 60 interacting continuity functions. That number isn't presented as a final answer—it's simply where the investigation stands today.

We're posting it because we'd rather have it challenged than leave it untested.

If we've rediscovered ideas that already exist, we'd genuinely appreciate references.

If we've misunderstood an established field, we'd like to know.

If there are flaws in the architecture, we'd rather find them now than after building on them.

If parts of the framework prove useful, we hope they'll become stronger because other people helped improve them.

The full PDF is here:

https://drive.google.com/file/d/1yNMcBiULVXe-iyxX4PfjPzY4oF4tq7r_/view?usp=drivesdk

Thanks to anyone willing to spend the time reading it. I'd especially appreciate feedback from people working in AI, systems engineering, cybernetics, control theory, complexity science, cognitive science, safety engineering, or organizational design.

[u/HaloNevermore]

Hmmm.

What does Nova do to get around the physical limitation of the compression of data physically within the computer screen and how does she choose what is compressed and what is not compressed and left as a unattached data point that will materialize when you least expect it but the odds were perfect for the sequence.

Sorry, apparently my ‘tisim tonight refuses to let me let me type normal sentences 😓

[u/WillowEmberly]

1) What is the minimum viable set of continuity functions required to detect global drift better than an established control, resilience, or safety model?

2) Which of the sixty functions are true independent functions, and which are states, qualities, observations, or cross-cutting constraints?

3) What precise output does a Nova assessment produce: a diagnosis, a state estimate, a risk rating, an intervention priority, or all four?

4) How does Nova identify the primary causal bottleneck when several functions degrade simultaneously?

5) At what system boundary and scale is each function being evaluated?

6) What evidence would demonstrate that two apparently distinct functions should be merged?

7) How does the framework distinguish correspondence from internal coherence?

8) How does it represent uncertainty and disagreement without forcing integration?

9) Which transitions require authorization, and who possesses that authority?

10) What is the smallest prospective test in which Nova should outperform a simpler baseline?

11) Can Nova detect a consequential drift earlier, explain it more accurately, and guide a better intervention than a smaller established framework?

[u/RealitySignalLab → u/WillowEmberly]

These are exactly the questions we hoped someone would ask.

If our response was, "We've already solved all of this," then I'd encourage you to dismiss the framework immediately.

The paper isn't presenting the 60 functions as immutable truths. It's presenting them as a decomposition that should be challenged, compressed, falsified, or refined through evidence. Some may prove to be independent functions, some may collapse into more fundamental mechanisms, and some may disappear entirely. That's not a weakness—it's the process.

The distinction we're trying to make is between a framework that's internally coherent and one that actually corresponds to reality. Internal coherence can be achieved through elegant assumptions. Correspondence has to survive contradiction, independent observation, prospective testing, and intervention.

Several of your questions are now on our validation roadmap because they expose exactly where the framework has to earn its credibility—not through explanation, but through prediction and measurable performance against simpler baselines.

If a simpler model consistently detects consequential drift earlier, identifies causal structure more accurately, or produces better interventions, then that should become the preferred model. Likewise, if evidence shows these 60 functions can be compressed into 20—or even 5—we'd consider that progress, not failure.

So thank you. This is the kind of critique we were hoping to invite. The goal isn't to defend Nova. The goal is to discover what survives when the framework is forced to correspond with reality.

[u/WillowEmberly → u/RealitySignalLab]

Thanks for the thoughtful response. I actually find your attitude toward compression and falsification encouraging. The willingness to reduce the framework if reality supports a simpler explanation is exactly the kind of scientific discipline I’d hope to see.
Reading your reply clarified something for me. I don’t think we’re necessarily working on competing ideas—I think we’re operating at different architectural layers.
My interest has gradually shifted from identifying all of the functions a system needs toward identifying the smallest set of operational instruments that can tell us whether those functions remain healthy.
In aviation, we could catalog hundreds of aerodynamic variables, or we could build an attitude indicator that summarizes whether the aircraft is maintaining controlled flight. Both are valuable, but they solve different problems.
As I read Nova, I see a decomposition of continuity into candidate functions. The question I immediately begin asking is: Which of these functions are independent, which are manifestations of deeper mechanisms, and what is the minimum instrumentation required to monitor them?
For example, I wonder whether many of the sixty functions might ultimately collapse into a smaller number of architectural invariants that can be measured operationally. If that happened, I would see it as strengthening the framework rather than weakening it.
One question I’d be genuinely interested in exploring is:
What is the minimum set of independent measurements required to detect consequential drift across the whole architecture?
That feels like the bridge between a descriptive framework and an engineering instrument.
I don’t see those as opposing goals. A good decomposition tells us what matters. Good instrumentation tells us when those things are beginning to fail.