EasyJournal: An AI-Assisted Publishing Experiment

Over the last 18 months, I've extensively experimented with building applications using AI-assisted environments. In just the past six months, the capabilities of these AI tools have dramatically accelerated, prompting me to explore just how effectively one person—without engineering support—could quickly develop a simple yet practical journal platform. EasyJournal is the result of this experiment - https://easyjournal.org/.

EasyJournal was developed as a "go it alone" effort, leveraging my domain expertise in scholarly publishing and working closely with various AI agents. It was highly informative, revealing both what's currently possible with AI and where limitations remain.

About EasyJournal

EasyJournal provides intuitive tools for submission, peer review, editorial workflows, and publishing, all within a minimalist, accessible interface.

Designed specifically for scholars and independent researchers who seek simplicity without compromising functionality, EasyJournal emphasizes rapid setup and ease-of-use, allowing researchers to focus on scholarship rather than technology.

You can try the demo here: https://demo.easyjournal.org.

Throughout multiple iterations, I gained deep insights into AI workflows, agent quirks, and the realities of AI-generated code. AI outputs come fast and are functional but typically result in messy, unpredictable code beneath the surface. Fortunately, collaborating closely with experienced engineers allowed me to evaluate these outcomes thoroughly.

Our conclusions: AI-driven rapid prototyping is incredibly powerful and efficient. However, using AI-generated code directly in production is problematic, usually necessitating significant rewriting or refactoring.

A Hybrid Workflow: Rapid AI Prototyping with Engineering Refinement

To address these realities, we've begun developing workflows that combine rapid AI prototyping with dedicated engineering review and refinement. This hybrid approach enables rapid, iterative feature development while ensuring the final product is scalable, robust, and maintainable.

These insights have directly informed our strategic approach to software development at Kotahi, our scholarly communication system. Instead of relying on generic CMS solutions, we're now rapidly prototyping custom user interfaces. This significantly shortens development cycles, reduces iteration, and allows us to quickly deliver practical, tailored solutions. When the time is right, we involve engineers to ensure scalability, maintainability, and robustness.

There's a lot more to unpack here—I've learned a ton from this journey, particularly about how AI-driven prototyping can transform scholarly publishing workflows. I'll be writing more about these developments soon. In the meantime, if you're interested in exploring how similar strategies might work for your projects, please feel free to reach out—I'm always happy to share insights or chat about possibilities.

In the meantime, EasyJournal remains 100% open source and freely available (https://github.com/Shippies-org/easyjournal-py) —caveats and all—for anyone wishing to use it.

adam@adamhyde.net