Thinking of Joining the MVP Program? Hear What Makes It Special!
We’re thrilled to share our brand-new video spotlighting the heart of the MVP Program - our MVPs themselves! In this inspiring video, MVPs from around the world open up about what being part of this global community means to them, and why they love it. Watch the MVP Program video here If you’ve ever wondered what it’s like to be an MVP - or if you're considering applying - this is the perfect place to start! But that’s just the beginning. We’ve gathered a set of helpful resources to guide you through the program and how to get involved: New to the MVP Program? Start Here: MVP Communities Website – Find everything you need to know about the MVP Program, including how to apply, who the MVPs are near you, and the impact they’re making in their communities. MVP FAQs - Our updated FAQ page answers key questions about the application process, eligibility, expectations, and more. Live Event Replay - Don’t miss the replay of our recent live session, where MVPs Anastasia Salari and Zaid Zaim share their personal journeys, practical advice, and tips for those thinking about applying. Ready to Take the Next Step? If you’ve been actively contributing to the community over the past 12 months, this might be your moment. Whether through sharing knowledge, helping others, organizing events, or driving conversations - you’re exactly who the MVP Program is looking for. Dive into the resources, get inspired by the stories, and if you meet the criteria, consider applying or connecting with someone who can nominate you. Your journey to becoming an MVP could start today!Building Custom Chat AI: A Comprehensive Guide for Developers
In today's rapidly evolving digital landscape, the integration of artificial intelligence (AI) into business operations has become a pivotal strategy for companies aiming to enhance their customer engagement and streamline their processes. This article delves into the foundational steps and considerations for developers embarking on the journey of building a custom chat AI for their company website. From understanding the core concepts of AI to selecting the right models and implementing effective prompt engineering techniques, this guide provides a comprehensive overview to help developers navigate the complexities of AI development. Whether you are a beginner or have some experience in the field, the insights shared here will equip you with the knowledge and tools needed to create a robust and efficient chat AI tailored to your business needs. A discussion will be held with Nitya Narasimhan, Senior Cloud Advocate at Microsoft specializing in AI, and Wey Gu, a Chinese AI MVP, to delve into these critical topics. What are the first steps a developer should take when starting to build a custom chat AI for their company website? Nitya: If you are new to AI, start by familiarizing yourself with the core concepts and usage of AI models. A course like Generative AI for Beginnerscan be a great starting point. Next, get hands-on experience with models by trying out GitHub Models, which are free to use with just a GitHub account. This will help you build your intuition for model selection and prompt engineering. If you already have some experience, the initial steps to building a custom chat AI are as follows: Identify the use case and requirements (e.g., typical questions asked and valid responses). Choose a model to start prototyping (test the question with various models and compare results). If your chat AI is grounded in your data, identify the data sources and formats (where and what). Select an AI app template to jumpstart development and customize it with your model and data choices. How does understanding model choice impact the development of a custom chat AI? Nitya: Understanding model choice is crucial for developing a custom chat AI. It involves evaluating models based on three key factors: cost, customization, and performance. Customization: Start by identifying the task you want to execute (e.g., chat, image, embeddings, agents). Filter models that support this capability and validate them with a test prompt to ensure they fit your requirements. This process will narrow down your options from thousands to a few suitable models. Cost: Consider whether the model supports serverless deployments (pay-as-you-go, per token) or managed deployments (subscription-based, per VM). Evaluate costs not just for usage (chat completion) but also for end-to-end development (evaluations, iterative ideation). Performance: Assess models based on latency (e.g., chat completions vs. reasoning models) and the quality and safety of responses. Understand default model characteristics (model card) and perform custom evaluations to ensure quality for your desired prompts dataset. Can you explain the concept of prompt engineering and how it can be applied using GitHub models? Nitya: Prompt engineering involves guiding the model on how to process questions and generate responses to improve quality. Think of developers as teachers and models as students being taught to answer exam questions. Prompt engineering provides a rubric to guide models in giving relevant answers. This includes providing examples, creating personas (e.g., "answer politely using formal language"), defining output formats (e.g., "answer in 1-2 sentences", "reply with results in JSON format"), and configuring model parameters (e.g., temperature, stop-words, top-p, max tokens). When working with GitHub models, you can configure models using the Playground (UI) or move to an IDE with the Azure AI Inference API, offering both low-code and code-first options for prompt engineering. What is retrieval augmented generation (RAG), and how does it enhance the ability to chat with data? Wei: RAG involves grounding user questions in retrieved knowledge from private data sources to ensure responses are relevant to the application scenario. It works by wrapping the initial user prompt in a prompt template to create the final model prompt sent to the model. The RAG workflow includes retrieval of knowledge, augmentation of the prompt, and generation of the response. This dynamic process provides relevant grounding data and instructions to contextualize user questions for app-required responses. What are some practical tips for developers to streamline their end-to-end journey from catalog to cloud? Nitya: Here are three tips to get started: Model Selection: Use GitHub Models with diverse test prompts to build intuition for prompt engineering and model capabilities. Compare models side-by-side. Copilot Development: Start with an Azure AI app template. Deploy it to understand the application and its architecture before customizing it to your needs. Validate your development environment and get familiar with tools. Safety & Evaluation: Explore built-in content safety filters and evaluators in the Azure AI platform to understand metrics and effectiveness of your prompt engineering or RAG strategy. Use tracing and App Insights to monitor performance and cost. What are some common challenges developers might face when building a custom chat AI, and how can they overcome them? Nitya and Wei: There are many challenges we can think of - here are three that are important: App Architecture: Understand the app architecture for your scenario (e.g., RAG, multi-agent). Explore existing AI app templates to build intuition and customize one that fits your requirements. Model Choice: Choose models based on cost, quota availability, and flexibility for future configuration. Use the Azure AI model inference API to abstract provider-specific SDKs and decouple your code from your choice, allowing for easier model swaps later. Observability: Debug issues in app development or execution performance. Use platforms and tools that bring observability to the end-to-end workflow. Activate App Insights and use tracing tools to generate telemetry for insights locally or in production. What resources and samples are available for further exploration into this subject? Wei: Explore Azure AI App Templates, For Beginners Curricula, RAG Chat Workshop, AI Tour Workshops and Generative AI for Beginners. For more workshops and talks, visit https://aka.ms/aitour/repos. Feel free to check out opensource projects like AutoGen, LlamaIndex, LangChain, and CamelAI's documentation. As we conclude this exploration into building a custom chat AI for your company website, it's clear that the journey is both challenging and rewarding. By understanding the core concepts of AI, selecting the right models, and mastering prompt engineering, developers can create a powerful tool that enhances customer engagement and streamlines business operations. The insights and practical tips shared in this article provide a solid foundation for embarking on this journey. Remember, the key to success lies in continuous learning and adaptation. As AI technology evolves, you should also adapt your approach to developing and refining your chat AI. Stay curious, stay innovative, and most importantly, stay committed to delivering the best possible experience for your users.From Neural Networks to Community Engagement
My (MVP Gavita Regunath) fascination with technology started during my final year at university, when I worked on a project to develop a neural network that could detect leukaemia cells. It might sound intimidating, and it certainly felt that way at first, but I soon realised there was something magical about using lines of code to tackle real challenges. It opened my eyes to the power technology can have in making life better for so many people. My passion for community engagement came later, thanks to a few brilliant directors at Advancing Analytics named Simon and Terry who showed me how leadership can be both ambitious and compassionate. However, my children were the real spark that pushed me to visit local schools and show children that coding is not terrifying at all. I often compare it to building with Lego pieces, only you do not have to crawl under the sofa to find the missing bits. In my mind, technology is for everyone. It is not just for the stereotypical people you see in films tapping away at futuristic screens. Challenges and Triumphs I wish I could say my journey was all smooth sailing and celebratory takeaway nights, but being a woman in tech sometimes feels like being a very small fish in a very big pond. Early on, I had moments when I felt I was shouting to be heard, yet I kept reminding myself why I loved this field. It was the thrill of bringing new ideas to life and the support from kindred spirits who believed in me. One of my proudest moments was seeing my team members blossom into community champions in their own right. It is amazing to watch them share what they have learnt and inspire others in turn. That beautiful cycle of growth and support is the main reason I still leap out of bed every morning, excited to see what is next. Motivation and Values If I had to sum up what drives me, it would be a keen appetite for learning and a rather competitive streak that helps me aim for success. I like to think I use that competitiveness for good rather than evil. Every challenge is a chance to acquire new knowledge, and every milestone reached feels like hitting a hidden treasure in a quest. More importantly, I love sharing every insight I gain, because there is no point being the only person in the room who has all the answers. I also believe deeply in empathy and collaboration. The best solutions appear when people feel safe speaking up, and when every perspective is valued. I always say we are only as strong as those around us. If we help each other, we can create an environment where curiosity and creativity thrive, and no one ever feels silly for asking a question. Community Engagement and Belonging For me, community is all about open and honest conversation. I enjoy giving talks in schools, online forums and in person, because I remember what it was like to feel a bit lost when I was starting out. If I can make technology more approachable for someone else, I have done my job. A moment that truly made me smile was when a former student told me they had gone on to study AI after attending a small coding workshop I had helped organise. It was only a few hours out of my day, yet it set off a chain reaction that shaped their future. It is moments like these that remind me how one small act of sharing knowledge can grow into something much bigger. Lifelong Learning and Keeping Up to Date Technology never stops evolving. One day you are reading about a new AI breakthrough, and the very next day there is an update that makes it seem outdated already. I keep up by reading articles on the Microsoft Tech Community site, joining AI groups and following interesting people on LinkedIn. You have to sift through a bit of fluff now and then, but you also come across some genuine gems of wisdom. One of my favourite pieces of advice is this: if you really want to master something, teach it. When you explain a concept to someone else, it forces you to understand it on a deeper level. You realise where your own gaps are, and it encourages you to fill those gaps so you can pass on accurate information. Personal Growth and Future Plans When I look ahead, I see many ways to keep encouraging and supporting thriving tech communities. I have a few ideas in mind, such as building more formal mentorship programmes that give newcomers a guiding hand, working with schools so children can see coding as a chance to be creative, exploring more international collaborations and diving deeper into the ethical questions around AI. The expansion of AI in daily life excites me the most. I believe future generations will grow up treating AI as quite ordinary, just as we treat smartphones today. If I can help them view AI as a helpful tool rather than a mysterious black box, I will have accomplished one of my main goals. Final Thoughts So that is my story in a nutshell. I hope it encourages you to see how powerful technology can be, but even more importantly, how amazing it feels to build a community around it. My wish is that you might feel inspired to start sharing your own knowledge and experiences, whether you are teaching a child how to code or collaborating with a global network of scientist. Each of us has something unique to offer, and when we pool our talents, wonderful things happen. If you ever want to chat or exchange tips and ideas, please reach out. I am always happy to connect. Thank you so much for reading, and here is to many exciting adventures in tech for all of us. MVP Gavita Regunath
