Loops
Also written: Agentic loops, Agent loops
AI systems that repeatedly perform a task, analyze results, and refine their approach.
Loops in AI mean a system keeps trying something, learning from it, and trying again to get better. Think of a student practicing a math problem. They solve it, check their answer, and if it's wrong, they try again using what they learned from the mistake.
This process helps AI improve at tasks like writing, coding, or even playing games. It's like a continuous cycle of doing, checking, and adjusting until the AI reaches a good outcome.
In AI, 'loops' refer to iterative processes where a system executes a task, evaluates the outcome, and uses that feedback to modify its subsequent actions or parameters. This is fundamental to many learning algorithms and agentic systems.
These loops can range from simple feedback mechanisms within a single model's inference step to complex agentic cycles involving multiple tools, observations, and planning stages. The efficiency and effectiveness of these loops are critical for achieving complex goals and adapting to dynamic environments.
AI agents are increasingly being designed to perform complex tasks that require iterative refinement. This involves agents repeating cycles of action, evaluation, and adjustment to achieve goals, as seen in coding, design, and scientific problem solving. The term 'loops' captures this essential process of repeated, self-correcting steps in agentic AI.
- Gemini 4 Argon and Google Antigravity: From 2D concept to 3D cathedralGoogle · Google for Developers on YouTube ·
- Best Practices GuidexAI · xAI Docs: Guides ·
- spark Gemini 3.6 FlashGoogle · Gemini Models ·
- Ep 871: Desktop Agent Lingo Simplified: Goals, Loops, Plans, Subagents and how it works in Codex and Claude Code (Start Here Series Vol 30)Anthropic · Everyday AI ·
- Claude computes a nine-loop amplitude in N=4 super-Yang-MillsAnthropic · Anthropic Research ·
- spark Gemini 3.5 FlashGoogle · Gemini Models ·
- Gemini 3.6 Flash | Gemini APIGoogle · Gemini Models ·
- Ep 806: Desktop Agent Lingo Simplified: Goals, Loops, Plans, Subagents and how it works in Codex and Claude CodeAnthropic · Everyday AI ·
- How We Use AI Is ChangingOpenAI · The AI Daily Brief ·
- Anthropic Claude
- Anthropic's documentation and podcast episodes explain 'loops' as a fundamental concept in understanding desktop AI agents, alongside goals and plans.
- Google Gemini
- Google Gemini uses 'loops' in the context of agentic tasks and coding cycles, highlighting faster and more cost-effective AI for these iterative processes.
- xAI Grok
- xAI Grok's best practices suggest using the Responses API to maintain reasoning history, which is crucial for effective multi-turn AI and agentic loops.
- Recursion
- Recursion involves a function calling itself, often with a base case
- Training Epochs
- Epochs are full passes through a dataset during training. Loops
The concept of iterative loops is fundamental to computer science and machine learning, appearing in algorithms like gradient descent and reinforcement learning. The application to AI agents is a more recent development.
Ask an AI assistant like ChatGPT to write a short story, then ask it to revise it based on specific feedback, like 'make the main character braver.' Observe how it adjusts the story based on your input, demonstrating a simple loop.
The Playbook: reusable how-tos, prompts, configs and tips pulled out of the news.
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- TemplateTemplate for building an AI tool tailored to your workA structured approach to defining and building a custom AI tool for specific business needs. · 15 min
- TemplateEvals CSV prompt list for agent skillsA CSV file template for listing prompts used in evaluating agent skills. · 20 min
- HeuristicDouble coding agent task completion with docs linksProviding coding agents with a documentation link significantly increases their task completion rate. · 2 min
Questions people ask
- How do loops help AI get better?
- Loops allow AI to try tasks, see what works and what doesn't, and then adjust its approach for the next try. This continuous improvement cycle leads to better performance over time.
- Are loops the same as AI training?
- Loops can be part of training, but they also happen when an AI is actively working on a task (inference). Training is about learning from data, while loops during inference are about executing and refining actions.
First seen on Subvolts Jun 8, 2026. Updated Oct 18, 2026. Written by an AI model from the items above and reviewed against them weekly; report an error.