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In Day 13 of the Engineering AI Agents series, we evolve our agents from free-text responses to structured output systems. Most AI agents generate unstructured text, which is difficult for applications to consume automatically. In this episode we build structured output agents that return strict JSON responses which can be parsed directly into C# models. This architecture enables automation, CI/CD integration, and enterprise-grade AI workflows. We implement this using: • .NET 8 • Semantic Kernel • Ollama Local LLM • Typed C# Models • Strict JSON prompting By the end of this video you will learn: ✔ Why free-text LLM responses are unreliable ✔ How to force structured JSON responses ✔ How to deserialize LLM responses into C# objects ✔ How structured output enables automated decision systems ✔ How this architecture works with both Local LLM and Cloud LLM 📚 Series Progress Engineering AI Agents Playlist: Day 0 – Local Agent Setup (.NET + Ollama + Semantic Kernel) Day 1 – Code Understanding Agent Day 2 – Code Review Agent Day 3 – Memory-Based Review Agent Day 4 – Rule-Based Severity Engine Day 5 – CI/CD Automation Agent Day 6 – Repo-Wide Review Day 7 – Test Case Generator Agent Day 8 – DevOps Failure Analysis Agent Day 9 – Multi-Agent Systems Day 10 – Supervisor Pattern Day 11 – Agent-to-Agent Communication Day 12 – Tool Plugins Day 12B – Strict Function Calling Day 12C – Intelligent Tool Arbitration Day 13 – Structured Output Systems #agenticai #aiengineering #semantickernel #dotnetai #ollama #aiagents #genai #llm #softwareengineering #aiarchitecture