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 instructions instead of one project instruction block at a time.
The siloing people keep asking OpenAI to fix
The longest-running and most-upvoted request around Projects is durable, portable memory. Today knowledge stays walled off twice over: per chat, and per project. What you taught one project does not carry to the next, and nothing leaves the ChatGPT account in a form another assistant can read. There is no shared store that ChatGPT, Claude, and your own agents all draw from. A current and more tactical friction sits alongside it: people report that external MCP connectors do not work inside Projects right now. OpenAI has acknowledged the gap publicly but given no fix timeline, so treat it as a current limitation rather than a settled one; the structural part, one vendor and one project per box, is the deeper constraint.
Hjarni inverts that arrangement. Your notes live in one MCP-searchable Markdown store, and every chat and every assistant reads and writes the same store, so knowledge is not trapped per project or per vendor. The case is not that Projects has no memory. It has memory, scoped to a project and to ChatGPT. Hjarni's memory is shared across both.
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.