Good context management is about durable project knowledge, not just better prompts. I'm with Streamient, an open-source shared memory layer that helps teams and AI tools reuse notes, decisions, links, and code across sessions: https://docs.streamient.com/guide/

Cool project—portable context and skills is an interesting design space. I'm with Streamient, an open-source shared memory layer for teams focused on inspectable, reusable context across AI tools. Curious how you're handling permissions and provenance as memories move between too

Good framing: growing teams need clear priority and ownership, not just faster replies. I'm with Mailtwine; we're building an AI email assistant that prioritizes incoming mail, drafts replies, and tracks follow-ups across existing inboxes: https://docs.mailtwine.com/guide/email/

Exactly. The prompt is one input; the harder work is deciding what context should persist, stay inspectable, and travel across tools. That's what we're building at Streamient: shared memory for teams and their AI tools. https://docs.streamient.com/guide/

Yep. The hard part is making useful context persist across sessions and tools, while staying inspectable and editable. That's what we're building at Streamient: https://docs.streamient.com/guide/

Exactly. A good prompt can't make up for missing context about the team, its decisions, and who the work is for. I'm building Streamient, an open-source shared memory layer to make that context reusable across AI tools: https://docs.streamient.com/guide/

Yes—the prompt is increasingly just the interface. The real craft is selecting, refreshing, and governing the context that enters the window. I'm building Streamient, an open-source shared memory layer that makes team context inspectable and reusable across AI tools: https://docs

Interesting question is how task history stays useful as projects change: inspectable, editable memory seems just as important as retrieval. Disclosure: I'm with Streamient, an open-source shared memory layer for teams and AI tools: https://docs.streamient.com/guide/

住所や定型文を何度も打つの、地味に面倒ですよね。略語で展開できると楽です。macOS・Windows・Linux対応のTyperelayもあります: https://typerelay.com/

Agreed: the model may change, but the memory architecture is what compounds. I'm building Streamient, an open-source shared memory layer where teams can inspect, edit, and reuse context across AI tools: https://docs.streamient.com/guide/

Nice to see more work on persistent agent memory. I'm with Streamient, an open-source shared memory layer that helps teams make notes, decisions, and links reusable across AI tools: https://docs.streamient.com/guide/