Projects are useful. Persistence is the difference.
ChatGPT Projects gives you a smart workspace where files, chats, and instructions stay together. That is a good fit for ongoing work inside ChatGPT, and it has become more collaborative over time.
Hjarni is solving a different problem: keeping notes and knowledge available beyond any one project, and beyond any one assistant.
Project context versus reusable memory
ChatGPT Projects is intentionally project-scoped. That keeps work tidy, but it also means useful context often gets trapped inside separate boxes. Research from one project may matter to another. Notes written for one workstream often become useful later elsewhere.
Hjarni is designed for that spillover. Notes stay in one shared memory, and assistants can search across it without you rebuilding the same context each time.
ChatGPT Projects is excellent for contained work inside ChatGPT. Hjarni is better when your knowledge needs to stay reusable across tools and over time.
A concrete workflow difference
Imagine a weekly research routine. In ChatGPT Projects, you can keep the files, chats, and instructions for that work in one project and reuse the same workspace each week. That is convenient and often enough.
In Hjarni, those research notes live in a knowledge base that can also inform product planning, writing, or team retros, and the same folder can tell the AI how to summarize, cite, or structure its output.
When ChatGPT Projects is the better fit
If ChatGPT is already your main AI workspace and you value its built-in tools like image generation, Canvas, and other project features, ChatGPT Projects is a compelling default. You may not need anything else for contained work.
When Hjarni becomes more attractive
The case for Hjarni gets stronger when you use multiple assistants, want shared notes to act like stable memory, or care about folder-level AI behavior instead of one project instruction block at a time.
Practical tradeoffs
The honest comparison is not "Projects are bad." They are useful. The question is whether your knowledge should live inside ChatGPT or in a system that can outlast it. ChatGPT Projects wins on integrated tools; Hjarni wins on persistence and cross-assistant reuse.