01 ::
AI Annotation Strategy
My approach encompasses rubric construction and evaluation, fine-tuning Golden Responses and casting a critical human eye over responses to verify honesty and integrity.
Read More→Practice: Four Disciplines
What I do, in careful detail.
My work sits at the intersection of language, instruction and judgement. By training models through RLHF (Rehearsed Learning through Human Feedback), my focus is to ensure that every LLM response produced checks the "4U" criteria - unequivocally correct, uniform, useful and understandable.
4U · UNEQUIVOCALLY CORRECT / UNIFORM / USEFUL / UNDERSTANDABLE
02 ::
Alignment Research
Studying the edge cases where helpfulness, honesty and safety collide, and producing reference responses that resolve them without losing warmth.
Read More→03 ::
Language Education
Accessible language to teach models that learn. Multi-step reasoning, gentle correction and the metaphors that make difficult ideas hold in the mind.
Read More→04 ::
Quality Assurance & Calibration
Verifying that every response meets the standard. The feedback loops, comparison frameworks and the attention to detail that keeps annotation honest at scale.
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