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Enrique Encinas

Enrique Encinas

Associate professor, Institute of Design, Oslo School of Architecture and Design

MishMash role: Member · WP1 , WP2 , WP7


MishMash Projects

Other projects

Latest results

Type

Book chapter

  1. Book chapter, 2026

    Rhythm and Residue: Vyping as Prompting Inside the Post-Discursive Interface

    Open access

    Enrique Encinas ; Andrew Morrison ; Alexander Refsum Jensenius ; Markéta Dolejšová ; John Hill

    Prompt engineering strategies emphasise clarity, specificity, and well-structured input, on the assumption that large language models (LLMs) require clean input to interpret user intent. But LLMs are pattern interpolators: they “absorb” noise through statistical reconstruction rather than strict symbol matching. Text-centric HCI has studied this tolerance for two decades without integrating it into prompt engineering as a resource. We introduce vyping as an intentional mode of prompting in which one types into LLMs at the speed of thought, without correction. We developed vyping through sustained first-person inquiry. It can be seen as a micro-practice inside a broader post-discursive turn in which meanings increasingly travel as rhythms and patterns through latent-space proximity rather than as precisely-formed symbols. The mismatch between current LLM interfaces and their (human) users has led to two common layers in implementation: (1) an orthographic residue at the interface (autocorrect, spellcheck, tidy-prompt guides), and (2) an impairment parse shadow at the training layer, a form of overalignment in which the model reads orthographic deviation as a sign that something is wrong with the user. Overall, we offer three attunements (ease, reach, and pulse) as alternatives to efficiency-first prompt engineering, and situate the practice within critical HCI traditions of seamful, frictional, and embodied interaction. The critique is structured around a seed prompt that suspends the impairment parse and makes vyping livable; its section headings are taken from the prompt’s own rules. A copy of the seed prompt is provided at the end.

  2. Book chapter, 2026

    The Perfect Wrong Note: Vyping and the Keyboard as Musical Interface for Human-LLM Interaction

    Enrique Encinas ; Alexander Refsum Jensenius

    Human interaction with large language models (LLMs) is commonly framed as information exchange, optimized for efficiency and correctness. This paper proposes a different framing: keyboard-as-instrument, where typing to an LLM becomes a form of musical practice. Drawing on the lineage of keyboard instruments, the action-sound framework, and the aesthetics of failure in jazz improvisation and glitch music, the paper introduces vyping (typing without looking) as a technique that treats degraded input as an expressive gesture. When a person vypes, inter-onset intervals and keystroke dynamics carry embodied information that the LLM can integrate, in a process closer to musical comping (responsive accompaniment) than to improvisation proper. Three artifacts (ll00mtube, clix-vibe, and KeyMeter) illustrate this approach, making the temporal and sonic dimensions of typing visible and audible. The paper argues that typos can function as grace notes: productive deviations that open new directions. It proposes reverence (nuance, grace, and respect) as a design orientation for human-AI interaction, while acknowledging the discomfort of caring for a tool entangled with extractive labor and concentrated corporate power.

Journal article

Music performance

Conference

  1. Conference poster, 2026

    TAO — Transductive Acoustic Organism: A Persistent, Self-Hosted AI Instrument for Artistic Research

    Enrique Encinas

    Poster presented at the opening conference of MishMash Centre for AI and Creativity. The poster presents TAO, a persistent artistic-research instrument assembled from open-weight models for multimodal language, music generation and sound generation, running on a single self-hosted machine. Developed with MishMash seed funding as research infrastructure, TAO addresses what AI infrastructure artists and cultural institutions need in order to work critically, experimentally and sustainably.

Visual arts

More results in NVA…