I began my career in academic linguistics, studying how people construct meaning through language. My research focused on metaphor, discourse, evaluation, and lived experience. I worked with real-world language data including interviews, conversations, transcripts, and corpora. My task was consistent: identify patterns, define categories, and make meaning visible.
Key idea
The core of my work has remained the same. I build structured systems that make meaning operational.
What Academia Taught Me
Academic research trained me in rigour. I learned to define concepts precisely, separate interpretation from evidence, and build analytical frameworks that others could follow and test. Much of my work involved developing taxonomies, structured ways of organising language phenomena so that patterns could be analysed systematically.
This required:
- Designing coherent and distinct categories
- Documenting decision criteria clearly
- Handling ambiguity without flattening nuance
- Maintaining consistency across large qualitative datasets
Although this work was academic, it was already a form of system design.
Why I Transitioned
I became increasingly interested in applying these frameworks beyond academia. As AI systems expanded, it became clear that models rely on structured human input. Annotation schemes, evaluation criteria, and transparent rules determine whether systems behave reliably.
The analytical discipline I had developed was directly transferable to this environment.
From Interpretation to Infrastructure
The shift into applied language systems was not a break with my past work. It was a reframing of it.
In research, I asked:
- How is experience expressed?
- What patterns recur across discourse?
- How can meaning be modelled systematically?
In applied work, I now ask:
- How should language be labelled for consistency?
- What taxonomy will scale across datasets?
- How can evaluation logic remain transparent and reproducible?
The intellectual foundation is unchanged. The implementation context is different.
What I Build Now
I work at the intersection of linguistics and system design. My projects include:
- Designing rule-based language frameworks
- Building structured taxonomies
- Supporting annotation and evaluation workflows
- Developing interpretable, deterministic prototypes
I am particularly interested in systems that remain explainable. Each decision should be traceable to explicit logic rather than opaque inference.
Where My Niche Sits
Finding my niche meant recognising continuity rather than reinvention. The analytical discipline developed in research became operational infrastructure.
My work sits between:
- Qualitative linguistic insight
- Operational system logic
- Human judgement
- Scalable design
Linguistics and technology are not separate domains. They are layers of the same problem: how meaning is structured and made actionable.
Looking Ahead
I continue to focus on framework design. My aim is to create systems that are rigorous enough for industry and grounded enough in linguistic insight to handle complexity responsibly.
Language technology depends not only on scale but on clarity. Clarity begins with how we define, annotate, and evaluate meaning.