Vibe coding for clinicians: democratising bespoke software development for digital health innovation
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arXiv
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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866911625096724480 |
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| author | Ong, Ariel Yuhan Livingstone, Iain Kilduff, Caroline Sevgi, Mertcan Merle, David A Ruffell, Eden Keane, Pearse A Antaki, Fares |
| author_facet | Ong, Ariel Yuhan Livingstone, Iain Kilduff, Caroline Sevgi, Mertcan Merle, David A Ruffell, Eden Keane, Pearse A Antaki, Fares |
| contents | Clinicians often face workflow problems that are perceived as either too bespoke or low stakes to attract commercial attention. Historically, most do not have the technical knowledge to address these problems, but the recent emergence of "vibe coding" presents a transformative opportunity. Vibe coding refers to the co-development of software using natural language prompts to large language models. It offers a pathway to create simple tools that address these real-world pain points, or to prototype more complex ideas. In this review, written by a group of early adopter clinicians with a range of programming expertise, we introduce vibe coding for clinicians (especially those with no or minimal coding experience) as a way of democratising innovation from the front lines. We discuss foundational skills, outline some common challenges, provide a practical step-by-step playbook, and illustrate this approach with some case examples, taking care to consider caveats and guardrails for deployment. We propose that vibe coding is more than a technical shortcut for beginners and is not a replacement for professional software developers. Instead, it can bridge the gap between clinical insight and technical execution, equipping clinicians with the ability to rapidly prototype digital health solutions most reflective of clinical realities. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_22604 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Vibe coding for clinicians: democratising bespoke software development for digital health innovation Ong, Ariel Yuhan Livingstone, Iain Kilduff, Caroline Sevgi, Mertcan Merle, David A Ruffell, Eden Keane, Pearse A Antaki, Fares Human-Computer Interaction Clinicians often face workflow problems that are perceived as either too bespoke or low stakes to attract commercial attention. Historically, most do not have the technical knowledge to address these problems, but the recent emergence of "vibe coding" presents a transformative opportunity. Vibe coding refers to the co-development of software using natural language prompts to large language models. It offers a pathway to create simple tools that address these real-world pain points, or to prototype more complex ideas. In this review, written by a group of early adopter clinicians with a range of programming expertise, we introduce vibe coding for clinicians (especially those with no or minimal coding experience) as a way of democratising innovation from the front lines. We discuss foundational skills, outline some common challenges, provide a practical step-by-step playbook, and illustrate this approach with some case examples, taking care to consider caveats and guardrails for deployment. We propose that vibe coding is more than a technical shortcut for beginners and is not a replacement for professional software developers. Instead, it can bridge the gap between clinical insight and technical execution, equipping clinicians with the ability to rapidly prototype digital health solutions most reflective of clinical realities. |
| title | Vibe coding for clinicians: democratising bespoke software development for digital health innovation |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2604.22604 |