ChatGPT & Claude native memory
you mainly need your AI to remember preferences and conversation context — coding style, dietary restrictions, project names. casual use.
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compare ·ChatGPT & Claude native memory vs. 3ngram
claude memory is great for 'remember my stack' and 'call me Olivia'.
it is not great for 'send the case study by Thursday' or 'what blocker did we leave unresolved in Cursor?' — that is not what it was built to do. chatgpt memory is a similar shape to claude's, and also locked to one platform. 3ngram works alongside both.
at a glance ·7 capabilities
ChatGPT & Claude native memory vs. 3ngram, side by side.
| capability | 3ngram | ChatGPT & Claude native memory |
|---|---|---|
| what it does | shared work memory + follow-through + workflows | remembers preferences and conversation context |
| memory model | typed — decisions, commitments, blockers, preferences | flat key-value / conversation summaries |
| follow-through | active — overdue tracking, stale commitments | none, passive recall only |
| reusable workflows | stored prompts executable via MCP | Projects / Custom GPTs (platform-locked) |
| cross-platform | yes, same memory across any MCP client | no, each platform's memory stays there |
| programmable | yes, full MCP API | no API for memory management |
| dashboard | full web dashboard | basic memory settings page |
3ngram
you want AI work carried forward across platforms — decisions, commitments, blockers, source context, and reusable workflows included.
native memory remembers preferences. 3ngram carries real work forward.
3ngram is not a replacement — it is the layer that keeps decisions, commitments, blockers, and source context from leaking across AI sessions.