cagangedik

Thanks! The problem isn’t AI chat, it’s tracking what the AI actually does to files.

Since we rely on MCP, starting with environments like GitHub and IDEs makes this tractable.

If we can own more of that surface (i.e. build our own tool), expanding beyond devs is definitely on the roadmap.

Thanks! You hit the nail on the head with the core approach. But to answer your first question: you can't 100% guarantee the AI will call the MCP. That's exactly why we don't rely on it alone. If the AI skips context, our fail-safes kick in: we track compliance to existing decisions using their IDs directly on file save via our IDE extension, and through our GitHub App on PRs. Regarding your second point on edge cases: when existing rules don't cover a situation, or a PR introduces a new pattern, we extract those changes as DRAFT decisions and leave them for human approval. AI proposes, humans decide. We keep enforcement entirely advisory-only. It warns you, but it never blocks a merge. Advisory-only isn't a compromise; it's the point. We want to make architectural drift visible, not act as a stricter linter. Down the road, if the project grows the way we want, we think the ultimate way to handle this context orchestration might be building our own IDE.

Thanks!

Thanks!

Thanks! claude-mem captures what the AI did locally and replays it next session, great for solo continuity. Hopsule works at the organizational level: shared memories, structured decisions with lifecycle and enforcement, synced across your team via MCP, IDE extension, or CLI. Different layers, can coexist.