Project summary

Current LLMs frequently suffer from sycophancy and concessive drift—they adapt to user biases or abandon logical consistency under prompt pressure. Because internal alignment methods (like RLHF) rely on probabilistic weights, they cannot guarantee strict output bounds.

My goal with AXIOM-1 (A1M) is to build and scale an external, weight-agnostic governance layer that evaluates model outputs in real time before release. It acts as a deterministic circuit breaker against logical degradation, structural failure, and sycophantic alignment shifts.

What are this project's goals? How will you achieve them?

The primary goal of this project is to eliminate sycophancy and concessive drift in stochastic Large Language Models (LLMs) by deploying an external, weight-agnostic governance framework (AXIOM-1 / A1M). Instead of attempting to modify model weights through internal alignment techniques like RLHF—which remain probabilistic—AXIOM-1 treats model outputs as provisional candidates that must satisfy structural and logical stability checks prior to release.

How will this funding be used?

The funding will be allocated across cloud compute, benchmark dataset curation, open-source infrastructure, and independent verification. Here is how the budget scales from the minimum viability threshold ($20,000) to full-scale execution ($100,000)

Who is on your team? What's your track record on similar projects?

Team:

I am leading this project as an independent researcher and solo founder, handling system architecture, core engineering, and empirical benchmarking.

Track Record:

https://orcid.org/0009-0001-2930-3609
 
(M.SφCDM) Towards a Unified Topological Theory of Stability: Emergent Golden Ratio as a Determinant for Cosmic Action and Microscopic Systems.

https://doi.org/10.5281/zenodo.20090819

A1M (AXIOM-1 Sovereign Matrix) for Governing Output Reliability in Stochastic Language Models

https://doi.org/10.5281/zenodo.19608960

https://huggingface.co/spaces/Samir333zoom/Axiom-1-Sovereign-Matrix

https://github.com/zoom333samir/Axiom-1-Sovereign-Matrix

A Universal Stability Criterion for Symbolic Complex Systems: Detecting Structural Deviation Before Catastrophic Collapse (USG)

https://doi.org/10.5281/zenodo.18883274

Governed Release Architecture for Controlled Excellence (GRACE)

https://doi.org/10.5281/zenodo.19256386

https://doi.org/10.17605/OSF.IO/296KP

Detecting Spurious Periodic Generalization in Neural Networks (PGVP)

https://doi.org/10.5281/zenodo.18576471

Universal Resonance Theory (URT): A 12.8 Hz Wave Unifying Dark Matter, Dark Energy, and Consciousness

https://doi.org/10.5281/zenodo.18601436

https://dx.doi.org/10.2139/ssrn.5996974

What are the most likely causes and outcomes if this project fails?

Most Likely Failure Causes:

High Latency Overhead: The real-time evaluation matrix introduces too much inference delay for ultra-low-latency production applications.

Evasion via Novel Prompt Trajectories: Complex or subtle sycophancy strategies in scaling models (70B+) bypass the structural verification metrics (USG/PGVP).

Industry Adoption Resistance: Developers choose to rely solely on internal training-time alignment (RLHF/DPO) rather than integrating an external governance layer

How much money have you raised in the last 12 months, and from where?

$0 in external funding. Over the last 12 months, this project has been 100% self-funded. All research, preprint publications, computational validation, and open-source infrastructure development to date have been personally financed by the author.