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AI Agents, Agentic Coding, Loop Engineering, Software Development, GLM-5.2, Z.ai, Product Vision, Developer Feedback, External Feedback, AI-native Teams, Reinforcement Learning, Sparse Attention, Long Context Models

1 curated reading tagged "AI Agents, Agentic Coding, Loop Engineering, Software Development, GLM-5.2, Z.ai, Product Vision, Developer Feedback, External Feedback, AI-native Teams, Reinforcement Learning, Sparse Attention, Long Context Models " — ranked by relevance with AI

The Batch – Issue 359: Loop Engineering and the Rise of Agentic Coding (June 26, 2026)

deeplearning.ai

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DeepLearning.ai’s The Batch newsletter discusses three iterative loops that guide building AI‑powered software products: the agentic coding loop, the developer‑feedback loop, and the external‑feedback loop. It also highlights Z.ai’s release of the open‑weights GLM‑5.2 model, a Mixture‑of‑Experts transformer optimized for long‑running agentic coding tasks.

TomorrowCoolArticle ~10 min
The issue explains a practical framework (loop engineering) that is directly applicable to teams building AI‑driven products and highlights a newly released state‑of‑the‑art open model (GLM‑5.2) that enables longer, more reliable agentic coding. Both the conceptual guidance and the model announcement are immediately useful for engineers, tech leads, and product managers looking to adopt or improve AI‑assisted development workflows.
AI agents, agentic coding, loop engineering, software development, GLM-5.2, Z.ai, product vision, developer feedback, external feedback, AI-native teams, reinforcement learning, sparse attention, long context models
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