Quality Assurance Genius
Automated testing suite with visual defect detection and CI/CD integration.
AI & Automation
AI fails when it stays in a demo and never enters the workflow that produces the work. The useful question is which operational step becomes better, safer or faster.
What problem exists?
The useful question is not 'can we use a model?' It is 'which operational step becomes better, safer or faster?'
Automation without ownership of the surrounding process creates a new dashboard nobody checks. Agents, visual QA and document intelligence only belong where a person or a pipeline can act on the output.
What do I build?
LLM-powered agents, automated quality systems and visual defect detection embedded into operational workflows and CI/CD.
Quality Assurance Genius is the public example of visual defect detection wired into CI/CD. Other AI work on this site lives inside farm telemetry, risk documents and operational assistants — always next to a system of record.
Why domain knowledge matters
Automation without ownership of the surrounding process creates a new dashboard nobody checks. Domain knowledge chooses the step worth automating.
I will decline a model that has nowhere to live. Production AI is an architecture and operations problem first.
Relevant Work
Projects in AI & Automation
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