Independent AI Systems Assurance Researcher · Altru.dev
I am an independent researcher and systems designer working through Altru.dev. I build software and study how increasingly capable technical systems can remain useful, understandable, and worthy of trust.
I am interested in the difference between a system looking convincing and us having good reason to believe what it claims. My public work communicates that interest without publishing protected implementation details or unpublished methods.
I tend to look beyond an isolated component and ask how the surrounding system behaves over time: what assumptions are being made, how the parts depend on one another, what changes under pressure, and what evidence would make me revise my view.
When I notice a pattern in one field, I sometimes ask whether the underlying relationship appears somewhere else. I do not treat analogy as proof. I use it to generate a question, then look for a way to test whether the idea survives contact with evidence.
I try to distinguish what I observed from what I inferred and to make room for evidence that contradicts my first explanation. A useful model should survive challenge, not depend on confidence.
Systems-development lifecycle thinking has influenced me since college. I became interested in how requirements, operation, change, maintenance, and failure shape whether a system remains useful over time.
I investigate questions around complex software and AI systems. Public descriptions stay intentionally high level unless a specific result or artifact has been deliberately released.
Altru.dev also produces apps, extensions, games, and services designed to solve real problems with clear privacy and usability boundaries.
When work is ready to be public, I publish the artifact, result, or update in the appropriate place. Private architecture and unpublished technical methods remain private.
My work often moves between software, systems design, privacy, operations, and other technical domains when the underlying problem crosses those boundaries.
My technical background predates my current AI research. I studied computer science and worked with technical support, Microsoft Access, SQL, and database systems before moving through controlled-environment construction and project work, and later ISO 17025 quality and calibration management.
Those environments repeatedly required attention to requirements, interfaces, documentation, verification, traceability, and failure. That experience continues to influence how I approach complex technical systems today.