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David Sprague

@corridordiagnostics

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Founder of Corridor, an independent AI diagnostic and assurance system focused on evidence-based evaluation of advanced adaptive and cognitive AI systems.

https://www.linkedin.com/in/davidsprague01
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About Me

I am the creator and project lead of Corridor, an independent AI diagnostics and assurance project focused on structural failure detection, evidence quality, and long-horizon evaluation of advanced AI systems. I have directed Corridor’s architecture, experimental design, validation strategy, and technical development using AI-assisted engineering tools, GitHub, Replit, Python-based testing, and structured evidence pipelines.

My research includes the SSRN paper “The Local Illusion vs The Structural Reality: Structural False Relief in Agentic Systems,” which introduces Structural False Relief—the idea that apparent local recovery in an agent can mask accumulating structural degradation over longer execution horizons. That work developed directly from Corridor experiments.

I am especially interested in trustworthy AI, cognitive architectures, machine consciousness research, and developing better methods for independently observing what advanced AI systems are actually doing beneath surface-level outputs.

Projects

Corridor. Deep diagnostics of agentic sytems

unfunded

About DavidBy David1
Toward a Superhuman, Open-Ended Alignment Auditor
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David Sprague

18 days ago

I came across your work on automated alignment auditing and thought there may be a useful overlap with a project I’m developing called Corridor. Your approach is focused on proactively creating scenarios that expose alignment failures. Corridor approaches the problem from the observation side, preserving evidence from agent runs, runtime intervention, provenance, and deeper longitudinal diagnostics when appropriate telemetry exists.

It occurred to me that the two approaches could potentially complement each other. Your auditor could generate difficult or novel scenarios, while Corridor could independently observe and analyze the resulting runs.

I’m currently looking for external research collaborations and would be interested in discussing whether a small future experiment between the two systems might be worthwhile.