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Feedback-Loop Patterns

What you'll be able to do

Decide how an agent should check and correct its own work before you build it, and know where each feedback loop breaks - the decision that comes before every agent that retries or asks for review.

⌁ The review and retry loops inside coding agents, support-automation approval queues, and LangGraph, Google ADK and AWS Strands agents.
Start this internship
Create an account to unlock the 6 sections, the workbench, and askThili.
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Sections

1. Feedback-Loop Patterns: Evaluator-Optimizer, Critic-Actor, Self-Healing, Human-in-the-Loop
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2. Lesson 1 - Evaluator-Optimizer: generate, score, improve
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3. Lesson 2 - Critic-Actor: critique item by item, fix item by item
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4. Lesson 3 - Self-Healing: diagnose the failure, then change strategy
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5. Lesson 4 - Human-in-the-Loop: pause, ask, resume
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6. Lesson 5 - Choosing a feedback loop
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Dig deeper

📄Self-Refine: Iterative Refinement with Self-Feedback (Madaan et al., 2023, arXiv:2303.17651)
paper
📄CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing (Gou et al., 2023, arXiv:2305.11738)
paper
📄Teaching Large Language Models to Self-Debug (Chen et al., 2023, arXiv:2304.05128)
paper
📄Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena (Zheng et al., 2023, arXiv:2306.05685)
paper
🔗Building Effective Agents - Anthropic Engineering
article
🔗Groq - free API keys for open models
docs