# The interpreter as developer: An autoethnographic design study of building a computer-assisted interpreting tool through human-LLM co-creation

arXiv: https://arxiv.org/abs/2610.16460 · HTML: https://mlsanity.com/paper/2610.16460/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
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- First posted on arXiv 12 Oct 2026.

## Abstract (arXiv)

Real-time AI captioning now serves audiences at multilingual events, yet computer-assisted interpreting (CAI) tools are still built for interpreters, rarely by them. This article reports an autoethnographic design study in which a professional interpreter with no programming training built a local-first CAI system through expert-led 'vibe coding', co-creating with an LLM architect and a coding agent. Analysis of the complete development dialogues shows how tacit professional knowledge, from segmentation to booth infrastructure, was externalized into design after generic defaults failed in use. In a demanding public scientific event, three mechanisms of in-booth appropriation emerge under a firmly human-led division of labor; telemetry from a first fully instrumented assignment shows a fully local chain sustaining a median translation latency of 0.94 s across 971 utterances. The case is read as lead-user innovation newly enabled by generative AI, with implications for the technological literacy of interpreters and the future of interpreter training.