Building a Copilot Code-First with Azure AI
Tags: azure, beginners, ai, thisweekinai
Published: 2024-03-07 16:10:10

---
title: Building a Copilot Code-First with Azure AI
published: true
description: Learn how @Azure AI helps developers build generative AI solutions end-to-end with a code-first approach, using their own data in this Tech Community blog post.
tags: azure, beginners, ai, thisweekinai
cover_image: https://dev-to-uploads.s3.amazonaws.com/uploads/articles/z04qiyybyjlty3dilmu7.png
canonical_url: https://techcommunity.microsoft.com/t5/ai-ai-platform-blog/a-code-first-experience-for-building-a-copilot-with-azure-ai/ba-p/4058659
series: This Week In AI News
---


**3 Resources To JumpStart Your Azure AI Studio Exploration:**

1. [My Tech Community Post](https://techcommunity.microsoft.com/t5/ai-ai-platform-blog/a-code-first-experience-for-building-a-copilot-with-azure-ai/ba-p/4058659?wt.mc_id=aiml-111581-ninarasi)
2. [My Learn Collection](https://aka.ms/ai-studio/collection)
1. [Azure AI Week on #60DaysOfIA](https://aka.ms/ai-studio/intelligent-apps)

Welcome to the eighth post in my [**This Week In AI News**](https://aka.ms/ai-news) series. Today, I want to talk about building generative AI applications **code-first** with the Azure AI platform. What does this mean and how does it help us make the paradigm shift to LLM Ops?

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## What is LLM Ops?

Traditionally, when we talk about AI applications we were referring to _machine learning_ solutions where we built custom models trained on relatively-finite datasets for our target use case. The deployed AI application would then be used to **make predictions**.

Today, when we talk about AI applications we typically mean _generative AI_ solutions based on large language models trained on massive datasets. Our focus is then on prompt engineering and fine-tuning these pre-trained models to **generate content**.

This has led to a paradigm shift from **ML Ops** to **LLM Ops** where the end-to-end application development lifecycle looks more like the picture shown below. Building these solutions now requires us to think about 3 phases:
 1. Ideation - define and build the basic experience
 2. Augmentation - evaluate and refine for quality
 3. Operationalization - deploy and use in production

This requires new tools, technologies and processes to streamline developer experiencea in building, testing, deploying & integrating, these apps.

![LLM Ops](https://techcommunity.microsoft.com/t5/image/serverpage/image-id/552316i571E7F652BBB7F1C/image-size/large?v=v2&px=999)

## What is Azure AI Studio?

[Azure AI Studio](https://learn.microsoft.com/azure/ai-studio/) tackles this challenge by providing a unified platform that supports the entire workflow from ideation (explore models, engineer prompts) to augmentation (build and manage AI projects) to operationalization (deploy & monitor solutions).

Want to get started exploring the platform? Check out the [Azure AI Studio UI](https://ai.azure.com) - a browser-based experience perfect for low-code developers. But if you're a professional developer, you probably want to have more control over the interactions, and potentially integrate additional libraries or features to enhance your solution. This is where having support for _code-first_ development helps.

![Azure AI Studio](https://learn.microsoft.com/en-us/azure/ai-studio/media/explore/ai-studio-home.png)



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## What does code-first development mean?

From the Azure AI Studio perspective, this means supporting command-line (CLI) and programmatic (SDK) interactions with the underlying Azure AI platform and resources. In February, the Azure AI team recorded this livestream talk which walks you through the process of building an enterprise copilot AI experience using a code-first approach on Azure AI Studio.

{% youtube UbJg7RNLi7E %}

Want a more complete picture of what is involved? Check out my [Tech Community Post](https://techcommunity.microsoft.com/t5/ai-ai-platform-blog/a-code-first-experience-for-building-a-copilot-with-azure-ai/ba-p/4058659?wt.mc_id=aiml-111581-ninarasi) from last month for a more detailed description of the tools, process, and resources to skill up on this topic. The tweet below has a preview of the post for convenience.

{% twitter 1765756581709312147 %}

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## Azure AI Week & AskTheExpert

But there's more. Keep an eye out on Mar 11-15 (next week) as we launch [Azure AI Week on #60DaysOfIA](https://aka.ms/ai-studio/intelligent-apps) - part of a multi-week campaign with events and activities focused on building intelligent apps. 

Then join us on March 21 for an [#AskTheExpert](https://reactor.microsoft.com/en-us/reactor/events/21694/?ocid=buildia24_AE_website) session we will take your questions live, share demos and discuss the generative AI developer journey!

🚨 [Register Now](https://reactor.microsoft.com/en-us/reactor/events/21694/?ocid=buildia24_AE_website) to attend.

![Ask The Expert](https://azure.github.io/Cloud-Native/img/60-days-of-ia/ate-2024-03-21.jpg)

This is an exciting time for developers, data scientists and entrepreneurs to go from ideation to operationalization and build intelligent generative AI experiences code-first!  Don't forget to check out the resources below to start skilling up!


---

**3 Resources To JumpStart Your Azure AI Studio Exploration:**

1. [My Tech Community Post](https://techcommunity.microsoft.com/t5/ai-ai-platform-blog/a-code-first-experience-for-building-a-copilot-with-azure-ai/ba-p/4058659?wt.mc_id=aiml-111581-ninarasi)
2. [My Learn Collection](https://aka.ms/ai-studio/collection)
1. [Azure AI Week on #60DaysOfIA](https://aka.ms/ai-studio/intelligent-apps)