Harness Comparison: How Claude Code, Cursor, Devin, And Antigravity Each Handle Memory

AI coding harnesses such as Claude Code, Cursor, Devin, and Antigravity increasingly act as persistent development collaborators, but they manage memory differently: Claude Code relies on hierarchical summaries, Cursor retrieves and injects raw code context, Devin preserves task progress through checkpoints and execution logs, and Antigravity organizes reusable artifacts such as plans, diffs, and diagrams. Each approach helps agents handle immediate or task-specific context but may struggle to retain architecture rationale, developer preferences, recurring constraints, and other durable knowledge across sessions, projects, or tools. The post presents Mem0 as a complementary long-term memory service that stores compact, metadata-scoped memories through read and write APIs, enabling agents to retrieve prior decisions and preferences before planning or coding and save new lessons at meaningful milestones. It proposes integrating Mem0 through prompt augmentation, event-driven memory updates, project and user scoping, and summaries derived from logs or artifacts rather than storing raw operational data, with the goal of creating a shared memory layer that can be used across multiple coding harnesses.

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