A Field Report on AI-Assisted Development of an Electron+SQLite Hospital Management System: A Taxonomy of 44 Pitfalls and 20 Lessons Learned

This experience report documents the development of a desktop hospital management system using Electron and SQLite over a period of six versions (V1.0 to V2.0). The development process was conducted through a series of AI-assisted sessions, where a human developer and an AI assistant collaborated iteratively. Through this process, we encountered and documented 44 distinct pitfalls that disrupted development. This report contributes a taxonomy of these pitfalls, organized into eight categories: PowerShell and Terminal Issues, Electron Framework Problems, SQLite Database Challenges, Build and Packaging Failures, Security Vulnerabilities, Frontend and SPA Errors, JavaScript Syntax Issues, and Financial System Design Flaws. For each category, we present the symptoms, root causes, and the golden rules that were established to prevent recurrence. We also derive 20 golden rules for practitioners. Our findings suggest that while AI assistants can significantly accelerate software development, the collaboration process itself introduces a new class of pitfalls that must be managed through disciplined documentation and context management. Author Name in English: Abdullah Abdulrab Abdullah Nasser Al-Tairi Author Name in Arabic: عبدالله عبدالرب عبدالله ناصر الطيري

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Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-16
DOI
https://doi.org/10.5281/zenodo.22802332
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
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article

A Field Report on AI-Assisted Development of an Electron+SQLite Hospital Management System: A Taxonomy of 44 Pitfalls and 20 Lessons Learned

Abdullah Abdulrab Abdullah Nasser Al-Tairi
Zenodo (CERN European Organization for Nuclear Research)
Artificial Intelligence in Healthcare and Education
article

A Field Report on AI-Assisted Development of an Electron+SQLite Hospital Management System: A Taxonomy of 44 Pitfalls and 20 Lessons Learned

Abdullah Abdulrab Abdullah Nasser Al-Tairi
article en

Abstract

This experience report documents the development of a desktop hospital management system using Electron and SQLite over a period of six versions (V1.0 to V2.0). The development process was conducted through a series of AI-assisted sessions, where a human developer and an AI assistant collaborated iteratively. Through this process, we encountered and documented 44 distinct pitfalls that disrupted development. This report contributes a taxonomy of these pitfalls, organized into eight categories: PowerShell and Terminal Issues, Electron Framework Problems, SQLite Database Challenges, Build and Packaging Failures, Security Vulnerabilities, Frontend and SPA Errors, JavaScript Syntax Issues, and Financial System Design Flaws. For each category, we present the symptoms, root causes, and the golden rules that were established to prevent recurrence. We also derive 20 golden rules for practitioners. Our findings suggest that while AI assistants can significantly accelerate software development, the collaboration process itself introduces a new class of pitfalls that must be managed through disciplined documentation and context management. Author Name in English: Abdullah Abdulrab Abdullah Nasser Al-Tairi Author Name in Arabic: عبدالله عبدالرب عبدالله ناصر الطيري

Zenodo (CERN European Organization for Nuclear Research)
Thamar University (YE)
Partnerships for the goals
Openalex Percentile: Top 14%
Artificial Intelligence in Healthcare and Education
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