{"twitter_thread": [{"content": "Ever wonder how to stop AI agents from spiraling into endless tool calls? Today I'm sharing 7 design patterns that keep them in check. Read on for can't-miss insights.", "media": [{"caption": "7 Must-Know Agentic AI Design Patterns", "url": "https://machinelearningmastery.com/wp-content/uploads/2025/10/mlm-bala-7-must-know-agentic-ai-design-patterns.png", "source_url": "https://machinelearningmastery.com/7-must-know-agentic-ai-design-patterns/", "title": "7 Must-Know Agentic AI Design Patterns", "s3_key": null, "s3_thumbnail_key": null, "type": "image", "id": 46881, "html": null, "carousel_h5": "7 Must-Know Agentic AI Design Patterns", "alt": null}]}, {"content": "1. Prompting & Context Patterns: Use few-shot, chain-of-thought, and role prompting to guide model behavior and reduce unintended loops. Clear instructions set expectations.", "media": []}, {"content": "2. Responsible AI Guardrails: Integrate safety checks, fairness rules & output verification to catch harmful or looping content before it derails your system.", "media": [{"caption": "a diagram of a system", "url": "https://imgopt.infoq.com/fit-in/3000x4000/filters:quality(85)/filters:no_upscale()/articles/practical-design-patterns-modern-ai-systems/en/resources/69figure-3-1747124801262.jpg", "source_url": "https://www.infoq.com/articles/practical-design-patterns-modern-ai-systems/", "title": null, "s3_key": null, "s3_thumbnail_key": null, "type": "image", "id": 243976, "html": null, "carousel_h5": "a diagram of a system", "alt": null}]}, {"content": "3. Loop Agents with Termination: Design workflow agents to run iteratively with defined exit conditions (max iterations or feedback signals) to prevent infinite cycles.", "media": [{"caption": "Loop Agent", "url": "https://google.github.io/adk-docs/assets/loop-agent.png", "source_url": "https://google.github.io/adk-docs/agents/workflow-agents/loop-agents/", "title": null, "s3_key": null, "s3_thumbnail_key": null, "type": "image", "id": 243977, "html": null, "carousel_h5": "Loop Agent", "alt": "Loop Agent"}]}, {"content": "4. AI Ops Monitoring & Versioning: Track performance metrics like latency and token usage, enforce prompt/model versioning, and set rollback strategies to catch looping behavior early.", "media": [{"caption": "a diagram of a system", "url": "https://imgopt.infoq.com/fit-in/3000x4000/filters:quality(85)/filters:no_upscale()/articles/practical-design-patterns-modern-ai-systems/en/resources/15figure-7-1747124801262.jpg", "source_url": "https://www.infoq.com/articles/practical-design-patterns-modern-ai-systems/", "title": null, "s3_key": null, "s3_thumbnail_key": null, "type": "image", "id": 243974, "html": null, "carousel_h5": "a diagram of a system", "alt": null}]}, {"content": "5. Intelligent Model Routing: Route requests to specialized, cost-effective models based on task complexity. This reduces unnecessary, repeated tool calls.", "media": []}, {"content": "6. Sequential Orchestration: Use a fixed, linear pipeline where each AI agent processes output from its predecessor. Deterministic steps help avoid uncontrolled loops.", "media": []}, {"content": "7. Self-Feedback & Planning: Empower agents with self-reflection and planning capabilities to evaluate their outputs and exit repetitive cycles when tasks are complete.", "media": []}, {"content": "Which design pattern do you think is most effective for stopping endless tool calls? Reply, retweet, or share your thoughts!", "media": []}]}

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