🧑‍⚖️ Human-in-the-Loop Design Pattern for AI Agents скачать в хорошем качестве

🧑‍⚖️ Human-in-the-Loop Design Pattern for AI Agents

Human-in-the-Loop Design Pattern Chapter: 00:00 Introduction 00:50 Human-in-the-Loop Design Pattern - architecture 01:53 Core idea of Human-in-the-Loop Design Pattern 03:00 Why Human-in-the-Loop Design Pattern matters 03:57 When to use Human-in-the-Loop Design Pattern 04:43 Limitations of Human-in-the-Loop Design Pattern 06:09 Examples in Bioinformatics domain 07:07 Hands on (Environment setup) 07:30 Define Agents 08:03 Connect agents in a Human-in-the-Loop workflow 09:16 Execute the pipeline 10:39 Summary and recap Code: https://github.com/prpanigrahi/ai_age... In this video, we explore the Human-in-the-Loop (HITL) Design Pattern, a critical approach for building AI agents that combine machine efficiency with human judgment 🤖➡️🧠. Not all decisions should be fully automated. In high-stakes systems, AI agents handle routine work autonomously but pause at critical checkpoints to involve human reviewers. Humans evaluate results, provide guidance, or grant approval before the agent continues. 🧠 In this video, you’ll learn: ✅ What the Human-in-the-Loop design pattern is ✅ How agent workflows pause, escalate, and resume ✅ Why accountability and oversight matter in AI systems ✅ When HITL is mandatory — and when it’s unnecessary ✅ Trade-offs in speed, complexity, and system design 📌 Human-in-the-Loop is especially important when: • Decisions have safety, ethical, or legal implications • Errors carry significant consequences • Subjective or contextual judgment is required 🧬 We also discuss bioinformatics and life-science use cases, such as: • Clinical variant interpretation approval • Diagnostic decision-support systems • Regulatory or compliance reporting • Genomic analysis pipelines requiring expert review ⚠️ Full automation isn’t always the goal. The best systems balance autonomy with accountability. 👉 This video concludes the Agentic AI Design Patterns series. Use these patterns as a practical toolkit for designing reliable AI agents.