Co-Founder @BuildCoherence | Building Axiom to elevate logical discourse and knowledge 🚀 | Husband of @RealMetaBiascoherencelabs.net USAJoined February 2026
Sure! First, I have to give a bit of a background. Roughly speaking, Axiom is a social media platform where the only content you can post is formally verified logic. This sounds intimidating, but it's really not! Formalized DOES NOT mean precise, and the finicky bits are handled by LLMs.
I'll use the concept of love, because it's one of those things that "can't be formalized". You can talk about love in formal logic without having to know exactly how to define it; you simply assert properties that you care about, over time as you need them.
For example, you might say "if x loves y, then x spends some time thinking about y". You could also take a transitive view of love and say "if you love someone, you love everyone they love". We can use these rules to provably deduce things that follow from those properties, and even find where your definitions are inconsistent.
These are exactly the sort of propositions that users in Axiom will be able to assert. We are aiming to make it easy to query aggregations so y'all can get real data on which "blue chip" props people are most willing to adopt.
Not only that, people can adopt inference rules that bind certain meanings to those props. This allows us to distinguish syntactical agreement from semantic agreement. That's the difference between us both supporting "free speech" but disagreeing on a law regarding when speech should be criminal.
Mechanically, that looks e.g. like the following: A person adopts both A: ("All people are capable of goodness") and B: (A → "Everyone should be given a chance at rehabilitation"). While some else adopts A but doesn't adopt B, or even rejects B by adopting ¬B. They agree on the syntax but not the semantics.
In short, it looks like moving to formal logic. A claim or argument is meaningful iff it has a logical representation. The two main barriers are how to transition incrementally and who decides the axioms. Our upcoming product @BuildCoherence solves both.
How it looks visually isn't a set thing. With a formal structure in hand, we can programmatically generate all sorts of visualizations. Argument flow charts and Euler diagrams are two great ones:
x.com/SemanticSamuel…
In Axiom, arguments are proven valid in Lean. Here, if you accept the 6 premise nodes, you must accept the conclusion.
The point is not that this is a perfect argument, it's that we can use this imperfect argument to pinpoint where our reasoning needs to be improved. Readers in
Am I the only avid AI agent user that doesn't even think about benchmarks? 67% vs 71% on DeepSWEBench Diamond?! Does this mean something to someone?
Fortunately at this point, my brain mostly filters out benchmark charts, as they've never proven helpful in informing my actions.
@deepfates We are @BuildCoherence. A prerequisite to human interpretability is having coherent and well-defined beliefs. Which is why we're developing a protocol for using using logical structure rather than prose as the substrate for communication.
@henriquebastos Refine it AND articulate it! There's all these principles of intuition/taste that we've never had to articulate, even when coaching jr devs, because humans share a lot of intuition. As those get articulated, AI will write better code.
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