Letta Code: A Memory-First Coding Agent for Persistent Learning Across Sessions
By
ascorbic
The bagel they save for the regulars. Don't skim, savour.
Summary
Letta Code is a memory-first coding agent designed for long-lived, persistent AI agents that learn and improve across multiple sessions rather than operating in independent sessions. It's a model-agnostic open-source harness that ranks #1 on the TerminalBench coding benchmark and achieves performance comparable to proprietary solutions from major LLM providers like Claude Code, Gemini CLI, and Codex CLI.
Key quotes
· 4 pulledLetta Code is a memory-first coding agent, designed for working with agents that learn over time.
Rather than working in independent sessions, each session is tied to a persisted agent that learns.
Letta Code is also the #1 model-agnostic OSS harness on TerminalBench.
Letta Code achieves comparable performance to harnesses built by LLM providers (Claude Code, Gemini CLI, Codex CLI) on their own models.
You might also wanna read
AgentMemory: Open-source persistent memory tool for AI coding agents
AgentMemory is an open-source tool that gives AI coding agents (like Claude Code, Codex, Cursor, etc.) persistent memory across sessions, so
DeltaMemory: A Persistent Memory Layer for AI Agents That Learns Over Time
DeltaMemory is a new AI memory layer designed to solve the problem of AI agents forgetting information between sessions. Unlike vector datab
Byterover: A Memory Layer for AI Coding Agents
Byterover introduces a memory layer for AI coding agents, enabling the creation, retrieval, and management of coding best practices across p
Claude Code Works Better When You Let Sessions Die
ContextPool: Persistent Memory Tool for AI Coding Agents
ContextPool is a tool that provides persistent memory for AI coding agents, addressing the problem of AI assistants starting each coding ses
CodeYam Memory CLI: AI-Powered Memory Management for Claude Code Development
CodeYam Memory is a CLI tool designed to improve Claude Code's performance by addressing repetitive mistakes and stale documentation. It use
