Comment by christinetyip
6 hours ago
I mostly agree with this, if the goal were “better persistent memory inside Claude Code,” that wouldn’t be very interesting.
For a single agent and a single tool, keeping project specs and decisions in markdown and explicitly pointing the model at them works well. We do that too.
What we’re focused on is a different boundary: memory that isn’t owned by a specific agent or tool.
Once you start switching between tools (Claude, Codex, Cursor, etc.), or running multiple agents in parallel, markdown stops being “the memory” and becomes a coordination mechanism you have to keep in sync manually. Context created in one place doesn’t naturally flow to another, and you end up re-establishing state rather than accumulating it.
That’s why we're not thinking about this as "improving Claude Code”. We’re interested in the layer above that: a shared, external memory that can be plugged into any other model and tools, that any agent can read from or write to, and that can be selectively shared with collaborators. Context created in Claude can be reused in Codex, Manus, Cursor, or other agents from collaborators - and vice versa.
If one already built and is using one agent in one tool and is happy with markdown, they probably don’t need this. The value shows up once agents are treated as interchangeable workers and context needs to move across tools and people without being re-explained each time.
If markdown in a git repository isn’t good enough for collaboration, then why would any plugged in abstraction be better?
You imply you have a solution for current wholistic state. For this you would need a solution for context decay and relevant curation — with benchmarks that prove it is also more valuable than constant rediscovery (for quality and cost).
That narrative becomes harsher once you pivot to “general purpose agents” because you’re then competing with every existing knowledge work platform. So you’ll shift into “unified context for all your KW platforms” - where presumably the agents already have access (Claude today can basically go scrape all knowledge from anywhere).
So then it becomes an offering of “current state” in complex human processes and this is a concept I’m not sure any technology can capture; whether it’s across codebases (which for humans we settled on git) and especially not general working scenarios. And I guess this is where it becomes a unified multi-agent wholistic state capture. Ambitious and fun problem.