ContinualCode: Claude Code That Learns from Corrections
Source: https://x.com (tweet) Author: unknown Date: 2025-2026
Summary
Inspired by SDPO, a minimal Claude Code fork that learns from user corrections in real-time using Tinker. When a diff is denied, the model uses the correction as context, takes a gradient step on LoRA weights, and retries. Minimal implementation of online continual learning for coding agents.
Key Claims
- Real-time learning from rejected diffs
- Correction → context → LoRA gradient step → retry
- Built on Tinker (RL training framework)
- Demonstrates continual learning without catastrophic forgetting (LoRA isolation)
- Minimal implementation — proves the concept is simple to build
Connection to Other Sources
Implements the concept from Continual Learning Problem (catastrophic forgetting). Uses LoRA to avoid forgetting. Relates to Cursor Real-Time RL — same idea but user-driven.
Concepts
- Coding Agents — online learning from user rejections
- RL Infrastructure — LoRA-based continual learning