Partner Blog | Build customer trust at scale with role-based certifications
As AI moves from experimentation to production, customers are raising the standard for what “ready” looks like. They want partners who can design and deliver solutions with security and responsible AI in mind, scope work accurately, and execute reliably across geographies and teams. In this environment, certifications are no longer a nice-to-have. They are a signal of capability and a practical way to build consistency at scale. A December 2025 Forrester Total Economic Impact™ study indicates that participating in Microsoft skilling and enablement initiatives can realize 217% ROI and $67.9M USD net present value over three years for a composite partner. For many partners, that maps to what customers are asking for right now: Prove you can deliver. Reduce risk. Do it consistently, even as technology and expectations keep moving. Continue reading hereAgentCon Hong Kong - Come One Come All for FREE
AgentCon is coming to Hong Kong! 🚀 The AI Agents Developer Conference lands on Saturday, 11 April 2026, at Hong Kong Institute of Information Technology (HKIIT) (VTC Tsing Yi Complex). If you're building with AI agents, automation, or intelligent systems, don't miss this gathering of developers, architects, and AI leaders for a full day of real-world sessions focused on designing, deploying, and scaling AI agents. Secure your spot ➡️ https://aka.ms/AgentconHongKong2026AgentCon Seoul - Come One Come All for FREE
AgentCon is coming to Seoul! 🚀 The AI Agents Developer Conference lands on Thursday, 16 April 2026, at Seoul National University. If you're building with AI agents, automation, or intelligent systems, don't miss this gathering of developers, architects, and AI leaders for a full day of real-world sessions focused on designing, deploying, and scaling AI agents. Secure your spot ➡️ https://aka.ms/agentconSeoul2026AgentCon London - Come One Come All for FREE
AgentCon is coming to London! 🚀 The AI Agents Developer Conference lands on Wednesday, 22 April 2026, at London Southbank University If you're building with AI agents, automation, or intelligent systems, don't miss this gathering of developers, architects, and AI leaders for a full day of real-world sessions focused on designing, deploying, and scaling AI agents. Secure your spot ➡️ https://aka.ms/agentconLondon2026Microsoft Partners: Accelerate Your AI Journey at AgentCon 2026 (Free Community Event)
Recently, a customer asked me a question many Microsoft partners are hearing right now: “We have Copilot — how do we actually use AI to change the way we work?” That question captures where we are in the AI journey today. Organizations have moved past curiosity. Now they’re looking for trusted partners who can turn AI into real business outcomes. That’s why events like AgentCon 2026 matter. A free, community-led event built by practicioners AgentCon is not a traditional conference. It’s a free, community-driven global event organized by the Global AI Community together with Microsoft partners and ecosystem leaders. Simply put: it’s for the community, by the community. Across cities worldwide, developers, consultants, architects, and Microsoft partners come together to share practical experiences building with AI agents, Copilot, and the Microsoft platform. The focus isn’t theory — it’s implementation: What worked What didn’t What partners can apply immediately with customers This peer learning model reflects how many of us actually grow in the Microsoft ecosystem: by learning from other partners solving real problems. Why this matters for Microsoft partners The opportunity for partners is evolving quickly. Customers aren’t just asking about AI tools — they’re asking how to redesign processes, automate work, and unlock productivity using AI-powered solutions. The Microsoft AI Cloud Partner Program emphasizes partner skilling and helping customers realize value from AI investments. Community events like AgentCon accelerate that learning by bringing partners together to exchange proven approaches and practical insights. When partners upskill faster, customers succeed faster. Why attend AgentCon is designed to help partners move from AI awareness to AI delivery. As an attendee, you can expect: Practical sessions and demos from practitioners Real-world AI and agent scenarios Direct conversations with builders and peers New collaboration and co-sell opportunities You’ll leave with ideas and approaches you can bring directly into customer engagements. Why speak AgentCon thrives because partners share openly with one another. If you’ve implemented Copilot, explored AI agents, or learned lessons from customer deployments, your experience can help others accelerate their journey. Speaking at AgentCon allows you to: Share your expertise with the global partner community Build credibility within the Microsoft ecosystem Create new partnerships and opportunities Contribute to collective partner success You don’t need a perfect story — just an honest one others can learn from. Join the global AgentCon community AgentCon 2026 events takes place around the world including these upcoming events: March 9 - New York: https://aka.ms/AgentconNYC2026 April 11 - Hong Kong: https://aka.ms/AgentconHongKong2026 April 16 - Seoul: https://aka.ms/agentconLondon2026 April 22 - London: https://aka.ms/agentconSeoul2026 Each event is locally organized, community-led, and free to attend. Help shape the next phase of AI adoption AI transformation is happening now — and Microsoft partners play a critical role in guiding customers forward. AgentCon is an opportunity to learn together, share experiences, and strengthen the partner ecosystem driving AI innovation. 👉 Register or apply to speak: https://aka.ms/agentcon2026 We hope you’ll join us — and be part of the community helping customers turn AI potential into real impact.AgentCon New York - Come One Come All for FREE
On March 9, 2026, #AgentCon lands at Nasdaq, Times Square, bringing together developers, engineers, and innovators shaping the future of AI agents. Expect deep‑dive talks, hands‑on learning, practical demos and plenty of networking with the AI community. This isn’t just another AI event, it’s where builders meet to talk real code. ➡️ Register now!APAC Fabric Engineering Connection
Excited to share what’s ahead for this week’s Fabric Engineering Connection sessions — your weekly opportunity to hear directly from the Microsoft Fabric engineering teams and stay ahead of what’s coming next in the platform. 🎙️ Featured Topics & Speakers: 🔧 Updates on DBT Job Abhishek Narain, Principal PM Manager 🤖 Upcoming Capabilities in Fabric Data Agents Misha Desai, Principal Product Manager Virginia Roman, Senior Product Manager Shreyas Canchi Radhakrishna, Product Manager 🌍 Americas & EMEA 📅 Wednesday, February 25 ⏰ 8:00–9:00 AM PT 🌏 APAC 📅 Thursday, February 26 ⏰ 1:00–2:00 AM UTC (Also available Wednesday, February 25, 5:00–6:00 PM PT) Whether you're deep in deployment, scaling customer workloads, or exploring new Fabric capabilities, these sessions are packed with insights to help you accelerate your practice. 👉 Not yet part of the Fabric Partner Community? Join here: https://lnkd.in/g_PRdfjt Let’s keep learning, building, and shaping the future of Fabric—together. 💡Americas & EMEA Fabric Engineering Connection
Excited to share what’s ahead for this week’s Fabric Engineering Connection sessions — your weekly opportunity to hear directly from the Microsoft Fabric engineering teams and stay ahead of what’s coming next in the platform. 🎙️ Featured Topics & Speakers: 🔧 Updates on DBT Job Abhishek Narain, Principal PM Manager 🤖 Upcoming Capabilities in Fabric Data Agents Misha Desai, Principal Product Manager Virginia Roman, Senior Product Manager Shreyas Canchi Radhakrishna, Product Manager 🌍 Americas & EMEA 📅 Wednesday, February 25 ⏰ 8:00–9:00 AM PT 🌏 APAC 📅 Thursday, February 26 ⏰ 1:00–2:00 AM UTC (Also available Wednesday, February 25, 5:00–6:00 PM PT) Whether you're deep in deployment, scaling customer workloads, or exploring new Fabric capabilities, these sessions are packed with insights to help you accelerate your practice. 👉 Not yet part of the Fabric Partner Community? Join here: https://lnkd.in/g_PRdfjt Let’s keep learning, building, and shaping the future of Fabric—together. 💡Level up your Python + AI skills with our complete series
We've just wrapped up our live series on Python + AI, a comprehensive nine-part journey diving deep into how to use generative AI models from Python. The series introduced multiple types of models, including LLMs, embedding models, and vision models. We dug into popular techniques like RAG, tool calling, and structured outputs. We assessed AI quality and safety using automated evaluations and red-teaming. Finally, we developed AI agents using popular Python agents frameworks and explored the new Model Context Protocol (MCP). To help you apply what you've learned, all of our code examples work with GitHub Models, a service that provides free models to every GitHub account holder for experimentation and education. Even if you missed the live series, you can still access all the material using the links below! If you're an instructor, feel free to use the slides and code examples in your own classes. If you're a Spanish speaker, check out the Spanish version of the series. Python + AI: Large Language Models 📺 Watch recording In this session, we explore Large Language Models (LLMs), the models that power ChatGPT and GitHub Copilot. We use Python to interact with LLMs using popular packages like the OpenAI SDK and LangChain. We experiment with prompt engineering and few-shot examples to improve outputs. We also demonstrate how to build a full-stack app powered by LLMs and explain the importance of concurrency and streaming for user-facing AI apps. Slides for this session Code repository with examples: python-openai-demos Python + AI: Vector embeddings 📺 Watch recording In our second session, we dive into a different type of model: the vector embedding model. A vector embedding is a way to encode text or images as an array of floating-point numbers. Vector embeddings enable similarity search across many types of content. In this session, we explore different vector embedding models, such as the OpenAI text-embedding-3 series, through both visualizations and Python code. We compare distance metrics, use quantization to reduce vector size, and experiment with multimodal embedding models. Slides for this session Code repository with examples: vector-embedding-demos Python + AI: Retrieval Augmented Generation 📺 Watch recording In our third session, we explore one of the most popular techniques used with LLMs: Retrieval Augmented Generation. RAG is an approach that provides context to the LLM, enabling it to deliver well-grounded answers for a particular domain. The RAG approach works with many types of data sources, including CSVs, webpages, documents, and databases. In this session, we walk through RAG flows in Python, starting with a simple flow and culminating in a full-stack RAG application based on Azure AI Search. Slides for this session Code repository with examples: python-openai-demos Python + AI: Vision models 📺 Watch recording Our fourth session is all about vision models! Vision models are LLMs that can accept both text and images, such as GPT-4o and GPT-4o mini. You can use these models for image captioning, data extraction, question answering, classification, and more! We use Python to send images to vision models, build a basic chat-with-images app, and create a multimodal search engine. Slides for this session Code repository with examples: openai-chat-vision-quickstart Python + AI: Structured outputs 📺 Watch recording In our fifth session, we discover how to get LLMs to output structured responses that adhere to a schema. In Python, all you need to do is define a Pydantic BaseModel to get validated output that perfectly meets your needs. We focus on the structured outputs mode available in OpenAI models, but you can use similar techniques with other model providers. Our examples demonstrate the many ways you can use structured responses, such as entity extraction, classification, and agentic workflows. Slides for this session Code repository with examples: python-openai-demos Python + AI: Quality and safety 📺 Watch recording This session covers a crucial topic: how to use AI safely and how to evaluate the quality of AI outputs. There are multiple mitigation layers when working with LLMs: the model itself, a safety system on top, the prompting and context, and the application user experience. We focus on Azure tools that make it easier to deploy safe AI systems into production. We demonstrate how to configure the Azure AI Content Safety system when working with Azure AI models and how to handle errors in Python code. Then we use the Azure AI Evaluation SDK to evaluate the safety and quality of output from your LLM. Slides for this session Code repository with examples: ai-quality-safety-demos Python + AI: Tool calling 📺 Watch recording In the final part of the series, we focus on the technologies needed to build AI agents, starting with the foundation: tool calling (also known as function calling). We define tool call specifications using both JSON schema and Python function definitions, then send these definitions to the LLM. We demonstrate how to properly handle tool call responses from LLMs, enable parallel tool calling, and iterate over multiple tool calls. Understanding tool calling is absolutely essential before diving into agents, so don't skip over this foundational session. Slides for this session Code repository with examples: python-openai-demos Python + AI: Agents 📺 Watch recording In the penultimate session, we build AI agents! We use Python AI agent frameworks such as the new agent-framework from Microsoft and the popular LangGraph framework. Our agents start simple and then increase in complexity, demonstrating different architectures such as multiple tools, supervisor patterns, graphs, and human-in-the-loop workflows. Slides for this session Code repository with examples: python-ai-agent-frameworks-demos Python + AI: Model Context Protocol 📺 Watch recording In the final session, we dive into the hottest technology of 2025: MCP (Model Context Protocol). This open protocol makes it easy to extend AI agents and chatbots with custom functionality, making them more powerful and flexible. We demonstrate how to use the Python FastMCP SDK to build an MCP server running locally and consume that server from chatbots like GitHub Copilot. Then we build our own MCP client to consume the server. Finally, we discover how easy it is to connect AI agent frameworks like LangGraph and Microsoft agent-framework to MCP servers. With great power comes great responsibility, so we briefly discuss the security risks that come with MCP, both as a user and as a developer. Slides for this session Code repository with examples: python-mcp-demoPartner Blog | January 2026 skilling kickoff: Turn readiness into growth
A new year is a natural planning moment. Partners are navigating various pressures and opportunities, including fast-moving AI, shifting cloud workloads, rising security expectations, and data becoming a bigger part of every solution motion. In that environment, skilling can’t be treated as an optional add-on. It’s a core business priority that supports what partners care about most: winning work and delivering it with confidence. That’s the lens I’d encourage you to bring into 2026 planning. Not what courses should we take, but what technical and sales capabilities do we need to build so we can execute more consistently across sales and delivery. How data makes the case for readiness and enablement In December 2025, Forrester Consulting published a Total Economic Impact study, commissioned by Microsoft, on the partner opportunity for the Microsoft skilling and enablement offerings. The study modeled a composite organization based on interviews with partners who experienced the offerings. Continue reading here
