Agents
Ralph loop
Ralph loop is an agentic workflow that resets context between iterations to reduce drift.
Quick definition
Ralph loop is an agentic workflow that resets context between iterations to reduce drift.
- Category: Agents
- Focus: automation and task completion
- Used in: Automating multi-step tasks that span tools or apps.
What it means
Each cycle re-establishes goals, gathers fresh context, and executes a focused step. The reset helps avoid compounding mistakes across long runs. In agents workflows, ralph loop often shapes automation and task completion.
How it works
Agents typically run a loop of planning, tool use, and evaluation. Each step updates state so the system can decide what to do next.
Why it matters
Agents help automate multi-step work by combining reasoning, tools, and memory.
Common use cases
- Automating multi-step tasks that span tools or apps.
- Coordinating search, retrieval, and execution to reach a goal.
- Running background workflows with human-in-the-loop checkpoints.
Example
Iterate: restate the goal, fetch current files, run one change, then re-evaluate.
Pitfalls and tips
Agents can drift if goals are vague or tool permissions are too broad. Clear success criteria and guardrails keep them reliable.
In BoltAI
In BoltAI, this shows up when you enable tools, agents, or automation features.