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Show HN: Hopsule – Persistent memory and decision layer for AI development

6•cagangedik•1h ago
Hi HN! I'm building Hopsule.

If you use AI coding tools like Cursor, Copilot, or Claude, you’ve probably seen this happen: The AI writes good code - but it ignores your architecture.

It doesn’t know: - why you chose a specific pattern - which conventions your team agreed on - which decisions are already locked in So it falls back to generic patterns, outdated examples, or random GitHub training data. Over time this slowly breaks the consistency of the codebase.

Most teams try to fix this with: - giant Markdown files - wiki pages - long prompts - Slack threads But those aren't machine-readable rules.

So we built Hopsule. Hopsule turns architecture decisions into enforceable context that AI tools must follow.

Example: Your team approves a decision: “All database access must go through the repository layer.” Hopsule records this as a rule and injects it into the AI context before code generation.

No giant prompts. No manual context stuffing. No architecture drift.

Website: https://hopsule.com Docs: https://docs.hopsule.com App: https://app.hopsule.com

Comments

firatcan•1h ago
It looks fairly useful for development! Quick questions what's the difference between you guys and any persistent development memory tools like https://github.com/thedotmack/claude-mem ?
cagangedik•1h ago
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.

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