Comment by christinetyip
10 hours ago
You’re right that reading the same markdown file is trivial, that’s not the hard part.
Where it stopped being trivial for us was once multiple agents were working at the same time. For example, one agent is deciding on an architecture while another is already generating code. A constraint changes mid-way. With a flat file, both agents can read it, but you’re relying on humans as the coordination layer: deciding which docs are authoritative, when plans are superseded, which tickets are still valid, and how context should be scoped for a given agent.
This gets harder once context is shared across tools or collaborators’ agents. You start running into questions like who can read vs. update which parts of context, how to share only relevant decisions, how agents discover what matters without scanning a growing pile of files, and how updates propagate without state drifting apart.
You can build conventions around this with files, and for many workflows that works well. But once multiple agents are updating state asynchronously, the complexity shifts from storage to coordination. That boundary - sharing and coordinating evolving context across many agents and tools — is what we’re focused on and what an external memory network can solve.
If you’ve found ways to push that boundary further with files alone, I’d genuinely be curious - this still feels like an open design space.
You're still not closing the gap between the problems you're naming and how your solution solves them?
> With a flat file, both agents can read it, but you’re relying on humans as the coordination layer: deciding which docs are authoritative, when plans are superseded, which tickets are still valid, and how context should be scoped for a given agent.
So the memory system also automates project management by removing "humans as the coordination layer"? From the OP the only details we got were
"What it does: (1) persists context between sessions (2) semantic & temportal search (not just string grep)"
Which are fine, but neither it nor you explain how it can solve any of these broader problems you bring up:
"deciding which docs are authoritative, when plans are superseded, which tickets are still valid, and how context should be scoped for a given agent, questions like who can read vs. update which parts of context, how to share only relevant decisions, how agents discover what matters without scanning a growing pile of files, and how updates propagate without state drifting apart."
You're claiming that semantic and temporal search has solved all of this for free? This project was presented as a memory solution and now it seems like you're saying its actually an agent orchestration framework, but the gap between what you're claiming your system can achieve and how you claim it works seems vast.