Is LoopCraft free to use?

Yes. LoopCraft offers a free tier for designing and exporting AI agent loop patterns. A Pro plan is available for advanced features.

What is Loop Engineering?

Loop Engineering is designing the control flow for AI agents: how they plan actions, observe results, and iterate. LoopCraft includes 11 pre-built patterns based on research from Anthropic, OpenAI, and others — including ReAct, Plan-Execute, Evaluator-Optimizer, Multi-Agent, and more. Design loops visually and export to LangGraph, OpenAI Agents SDK, AutoGen, or CrewAI.

Which frameworks can I export to?

LoopCraft exports to LangGraph (Python), OpenAI Agents SDK (TypeScript), AutoGen (Python), and CrewAI (Python). Each export produces working code you can run directly in your project.

Do I need to write code?

No. LoopCraft is a visual builder — you design loop patterns with a drag-and-drop interface and configure nodes without writing code. Code export to LangGraph, OpenAI SDK, AutoGen, and CrewAI is generated automatically and is optional.

What loop patterns are supported?

LoopCraft supports 11 agent loop patterns: ReAct (think-act-observe cycle), Prompt Chaining (sequential steps with quality gates), Routing (classify and direct inputs), Parallel Sectioning (independent subtasks in parallel), Parallel Voting (multiple runs for confidence), Orchestrator-Workers (dynamic task decomposition), Evaluator-Optimizer (generate-evaluate loop), Plan-and-Execute (plan then execute with replanning), ReWOO (variable passing between tasks), LLM Compiler (DAG-based parallel execution, 3.6x speedup), and Multi-Agent (collaborative agents with roles).

LoopCraft — Design AI Agent Loops Visually

Blog

In-depth articles on AI agent Loop Engineering

2026-08-136 min

How to Use Audio Loops Effectively in Music Production

A practical guide on selecting, layering, and processing audio loops to build professional-sounding tracks, from choosing the right source material to final mix integration.

2026-08-136 min

How to design conditional branches in agent loops without creating spaghetti

Branches accumulate quietly until a loop's control flow resembles a plate of spaghetti. Seven patterns — centralized routing, flat conditions, converging branches, mandatory defaults, logging, pruning, and splitting — keep branching legible.

2026-08-075 min

Where to place human approval gates in your agent loops

A practical method for deciding which steps need human sign-off: classify actions by reversibility, gate at boundaries, and keep loops moving while reviews are pending.

2026-08-065 min

A practical guide to setting token budgets for agent loops

How to measure a loop's baseline cost, choose alert and hard-limit budgets, and wire the Cost Budget Guard into loops with retries and sub-loops.

2026-08-034 min

Loop Versioning: How to Update a Live Loop Without Breaking Running Iterations

Use loop versioning to deploy changes to a loop definition while in-flight iterations continue on the previous version.

2026-06-229 min

Agent Evaluation at Scale: Beyond 'Vibe Checks' to Systematic Testing

Manual testing of AI agents doesn't scale. Learn how to build systematic evaluation pipelines with assertion-based tests, LLM-as-judge scoring, and production monitoring.

2026-06-218 min

Designing Fault-Tolerant AI Agent Systems: Patterns from Production

Production agent systems fail in predictable ways. Learn the retry, fallback, circuit-breaker, and human-in-the-loop patterns that keep agents running reliably.

2026-06-085 min

Why ReAct is Still the Foundation

Understanding the Thought-Action-Observation loop.

2026-06-047 min

Orchestrator-Workers vs Plan-and-Execute

A practical comparison of two powerful agent patterns.

2026-05-286 min

Building Reliable Agent Loops: Lessons from Anthropic

Key takeaways from Anthropic Building Effective Agents guide.

2026-08-055 min

When to add a retry layer to your agent loop

Transient API failures are inevitable.