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Sharda Kaur
Sharda Kaur

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Model Mondays Season 2 – For Developers: Episodes 1 to 5 Now Available

If you're a developer working with or exploring Generative AI, these first five episodes of Model Mondays Season 2 are packed with practical insights from Microsoft PMs and engineers. Topics include model reasoning, developer experience, model context protocols, and efficient deployment techniques.
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  1. S2E1 – Advanced Reasoning Recap** How advanced reasoning is evolving in modern LLMs and what it means for developers. https://techcommunity.microsoft.com/blog/educatordeveloperblog/s2e01-recap-advanced-reasoning-session/4425738?wt.mc_id=studentamb_263805

**2. S2E2 – Understanding Model Context Protocol (MCP)
**A look at MCP and how it gives developers better control over model behavior.
https://techcommunity.microsoft.com/blog/educatordeveloperblog/model-mondays-s2e2---understanding-model-context-protocol-mcp/4427914?wt.mc_id=studentamb_263805

**3. S2E3 – Understanding SLMs & Reasoning with Mojan Javaheripi
**Small Language Models (SLMs) and their real-world use cases for performance-sensitive apps.
https://techcommunity.microsoft.com/blog/educatordeveloperblog/s2e3-understanding-slms-and-reasoning-with-mojan-javaheripi/4429758?wt.mc_id=studentamb_263805

**4. S2E4 – Understanding AI Developer Experiences with Leo Yao
**What developers actually need when building with AI – from tooling to workflows.
https://techcommunity.microsoft.com/blog/educatordeveloperblog/s2e4-understanding-ai-developer-experiences-with-leo-yao/4431643?wt.mc_id=studentamb_263805

**5. S2E5 – Fine-Tuning & Distillation with Dave Voutila
**How to fine-tune large models and use distillation to create efficient versions for deployment.
https://techcommunity.microsoft.com/blog/educatordeveloperblog/model-mondays-s2e5-%E2%80%93-fine-tuning--distillation-with-dave-voutila/4433445?wt.mc_id=studentamb_263805

Stay tuned for new technical drops every Monday. Great content if you're building with Azure ML, working on custom copilots, or exploring efficient model deployment.

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