Meet Agent Ralph. Ralph is a brilliant AI coder. But Ralph has a weakness: his "Context Window" (short-term memory) is limited.
Normally, when you chat with an AI, you keep adding history. This causes Context Rot. As the history gets full, the AI gets confused, lazy, or starts hallucinating.
Objective: Overload Ralph. Keep asking him to code until he breaks.
CRITICAL FAILURE: Context Window Exceeded.
Most tools try to "summarize" old messages to save space. But summarizing code loses critical details (variable names, imports). This causes bugs.
The Ralph Loop takes a radical approach: Don't summarize. Die and Reincarnate.
Instead of one long conversation, we run a bash script that creates a fresh agent for every single step.
Interact: Change the input variable. Notice how the script stays outside the AI? The AI doesn't control the loop. The Loop controls the AI.
If we reset Ralph every time, he forgets what he just coded. We need External Memory.
We don't use chat history. We use Files.
Training Simulation: You are the Agent. Complete a task step, save it to disk, then die.
Let's put it all together. You are the Orchestrator (The Bash Loop).
We have a project with 4 tasks. Watch how Ralph wakes up, reads the files to understand context, does one task, saves, and dies. Then repeats.
You've successfully built a feature using the Ralph Loop.
Key Takeaways: