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Hopsule – Persisten Memory Layer for AI Engineering

Hopsule – Persisten Memory Layer for AI Engineering

by firatcan·Mar 19, 2026·5 points·1 comment
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AI Analysis

●●●BangerBig BrainSolve My Problem

Decision memory with enforceable context beats Cursor's built-in context features.

Strengths
  • •Capsules bundle exact decisions and memories into portable .capsule.json files with integrity hashes.
  • •Visual context graph traces code back to architectural decisions, not just git history.
  • •MCP integration means it works across Cursor, Copilot, and Claude without vendor lock-in.
Weaknesses
  • •AI context management is getting crowded with Continue, Cursor's own features, and MCP servers.
  • •Requires behavioral change — teams must capture decisions consistently for it to compound.
Target Audience

Developers building with AI coding agents

Similar To

Continue.dev · Cursor · Sourcegraph Cody

Post Description

Hey Everyone,

I'm neither the founder or affiliated with these guys. But when they showed me the product it really clicked a switch.

I have been building products with AI since sonnet 4.0, and one of my issue, like many, consistency.

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

Creates trackable, tasks which can be feed into your AI tools to do compound engineering.

If you're building with Claude Code, Cursor, or Copilot. You can use their CLI or MCP.

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