The “Coincidence Stack” essay is long, dense, and unusual. It mixes biblical texts, a bit of science fiction, state-of-the-art tech, philosophy, geopolitics, history, and statistics. You don’t have to agree with its conclusions to get value from it. Because it’s unusual and takes a winding path, this note is a brief user-guide.
1. What this is (and what it isn’t)
The essay is:
- A structured attempt to ask: “Is it even remotely plausible that biblical prophecy is tracking real history and near-future events?”
- A mix of text, timelines, and statistical modeling (Bayesian reasoning, Monte Carlo simulations).
- Written from a Christian perspective (I’m not an unbiased writer), but designed so a non-religious reader can still follow the logic. The math is just math—and in a sense it’s the guardrail for the entire experiment.
It is NOT:
- A demand that you share the author’s beliefs.
- “Believe or else” rhetoric.
- A finished academic monograph; it’s a serious working model exposed to critique.
Treat it as an argument to examine, not a doctrine you must swallow. It’s an experiment in the public domain.
2. How to engage the claims (especially if you’re skeptical)
You don’t need to be religious to read this honestly. A fair way to approach it:
- Treat it like any other big thesis:
What is the core claim?
What evidence is offered?
Which assumptions are doing the heaviest lifting? - Keep three layers separate in your head:
Textual – What do the biblical texts actually say?
Historical / astronomical – What happened and when?
Statistical – How are probabilities being assigned and combined? - Adjust the dials:
If the essay claims a 1-in-10ⁿ estimate, ask:
“What if I relax this?”
“What if some events aren’t independent?”
The point isn’t to accept numbers blindly, but to see how sensitive the conclusions are. - Notice when the author is speaking in conviction vs. calculation.
Some claims are explicitly faith-based; others are presented as “statistically overwhelming.” You can agree with one and question the other.
Take notes, mark friction points, and come back to them.
3. Using an LLM to help you read it
If you have access to an LLM (ChatGPT, Gemini, etc.), you can use it as a neutral assistant to unpack the essay, run the code, and stress-test the claims.
3.1 Suggested prompts
You can copy–paste these:
Load the essay
Prompt 1:Fetch: https://www.mwiya.com/the-coincidence-stack/
(Or paste the full text if your LLM can’t fetch URLs.)
Get a structured overview
Prompt 2:
“Review the essay as a whole, paying attention to all the detail and nuance. Give me a clear outline of its main claims and argument flow.”
Locate and run the code
Prompt 3:
“Identify the code in the Technical Appendix and run it in full. Tell me what it does and what outputs it produces.”
Verify Jewish day-count logic
Prompt 4:
“Make sure you have accounted for Jewish evening-to-evening day-count reckoning. The triple-lock day-count chiasm should be fully reconciled—confirm whether the triple-lock chiasm day counts match the claims in the essay.”
Run the sensitivity analysis
Prompt 5:
“Run the sensitivity analysis described in the body of the essay. Show me how the conclusions change as you vary the key parameters.”
Find the prior needed for 50% probability
Prompt 6:
“Identify the part of the essay that determines what prior is needed for the posterior probability to reach 50%. Explain that step in simple terms.”
Integrate math and theology
Prompt 7:
“Having run the code, the sensitivity analysis, and identified the prior needed for P = 50%, review the theology in the essay and consolidate your understanding of the overall argument.”
Ask for an evidence-anchored verdict
Prompt 8:
“Having run through this exercise, what do you think of the argument? Give me a response that is anchored only in the empirical and statistical evidence, and clearly separate that from any theological commitments.”
These prompts are useful whether you’re religious, agnostic, or atheist: they push the model to (a) make the structure explicit, (b) check the math, and (c) separate empirical claims from faith commitments so you can decide what you think.
3.2 Stress-testing the logic
Example prompts:
- “List the main assumptions in this essay’s probability model. For each one, show how the conclusions would change if the assumption were relaxed or made more conservative.”
- “Identify places where independence of events is assumed. Are these independence assumptions strong or weak? Justify your answer empirically.”
- “Play the role of a skeptical but fair statistician. Critique the Bayesian reasoning in this text.”
Here you’re not asking the AI to decide if prophecy is real, just to flag weak links in the reasoning chain.
3.3 Exploring alternative views
Example prompts:
- “Summarize how mainstream Christian theology would respond to these eschatological claims.”
- “Summarize how a secular historian might interpret the same historical data without invoking prophecy.”
- “Show me three alternative explanations for the ‘coincidence stack’ described here. All-in, being intellectually honest and given the evidence, sensitivity testing, priors testing, and astronomical considerations, what do you think?”
This gives you comparison points rather than a single narrative.
3.4 Deep dives on specific concepts
If a term is unfamiliar—Logos, Memra, Metatron, feast days, Bayesian priors—you can isolate it:
- “Explain the concept of ‘Memra’ in the Aramaic Targums and how it relates to ‘Logos’ in John 1, in neutral, historical terms.”
- “Explain what a Bayesian prior is, and how it’s used in this essay.”
- “The author talks about Monte Carlo simulations. Explain what those are in simple terms and how they apply here.”
Use the AI as a glossary and tutor, not as the final judge of spiritual claims.
4. How to read this if you’re religious / atheist / agnostic
If you’re religious (of any kind):
You already have a framework. Let this either challenge, sharpen, or refine it. You can ask: “If this is wrong, where exactly is it wrong?” rather than rejecting it wholesale.
If you’re atheist or agnostic:
You can treat this as a case study in how people build meaning, models, and forecasts from ancient texts. Your bar for evidence may be higher—that’s fine. The essay is still useful as data: a worked example of “applied eschatology + statistics.” Part of the goal is to provide a corpus of “proof of work” for how one might build a worldview and ontology under constraints of evidence.