Sr. Content Developer at Microsoft, working remotely in PA, TechBash conference organizer, former Microsoft MVP, Husband, Dad and Geek.
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Next-Level SQL in VS Code: GitHub Copilot Custom Instructions, Plan Mode & Skills | Data Exposed

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From: Microsoft Developer
Duration: 19:30
Views: 290

GitHub Copilot already generates awesome SQL code but awesome is different from aligned with your team. In this episode, we explore how to take full control of GitHub Copilot context inside VS Code using the MSSQL extension.

We start with a clean workspace to demonstrate what GitHub Copilot produces with zero context, then add a single custom instruction file that teaches it your team's exact T-SQL conventions automatically. We then use Plan Mode to design a full data model from a PRD (Product Requirements Document) and bring it to life in Schema Designer with Agent Mode, connecting GitHub Copilot to your actual database. From there, we create a skills file that teaches GitHub Copilot your vector search architecture as a slash command, generating SQL Server 2025/Azure SQL Database T-SQL without explaining anything in the prompt. To wrap up, we open the GitHub Copilot debug panel to inspect the full LLM request payload, including the system prompt and injected context, so you can see exactly what GitHub Copilot receives with every request.

Learn how to make GitHub Copilot and the MSSQL extension for VS Code work like a teammate who already knows your standards and architecture in this episode of Data Exposed.

0:00 Introduction
1:33 Demo
8:45 Demo
17:16 Demo
18:33 Getting started

✔️Resources:
Install: https://aka.ms/vscode-mssql
Demos: https://aka.ms/vscode-mssql-demos
Blogs: https://aka.ms/vscode-mssql-blogs
Documentation: https://aka.ms/vscode-mssql-docs

📌 Let's connect:
Twitter - Anna Hoffman, https://twitter.com/AnalyticAnna
Twitter - AzureSQL, https://aka.ms/azuresqltw

🔴 Watch even more Data Exposed episodes: https://aka.ms/dataexposedyt

🔔 Subscribe to our channels for even more SQL tips:
Microsoft Azure SQL: https://aka.ms/msazuresqlyt
Microsoft SQL Server: https://aka.ms/mssqlserveryt
Microsoft Developer: https://aka.ms/microsoftdeveloperyt

#AzureSQL #SQL #LearnSQL

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alvinashcraft
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Episode 425 – Exploring Collaboration and Governance at the MVP Summit with Joy Apple

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Welcome to Episode 425 of the Microsoft Cloud IT Pro Podcast. In this audio and video episode recorded live at Microsoft headquarters during the MVP Summit, Ben welcomes a return guest, Joy Apple, to the Microsoft Cloud IT Pro Podcast and discuss her 20-year career in the Microsoft collaboration space, from financial services to SharePoint training, consulting, and her current role at Orchestry Software. Joy explains Orchestry as a Microsoft 365 governance automation layer covering templated provisioning for SharePoint and Teams, archiving policies (including Microsoft 365 Archive), guest management, and OneDrive governance. They emphasize that AI and Copilot amplify existing information architecture, permissions, and data hygiene issues, making governance more critical. They describe the MVP Summit as a “family reunion” where MVPs attend sessions and reconnect with peers. Joy and Ben also spend some time describing paths becoming an MVP and how much they just enjoy the community around the Microsoft 365 ecosystem and connecting with people both at MVP Summit as well as various conferences throughout the year.

About Joy Apple

Joy is a Microsoft MVP and Director of Success and Enablement at Orchestry. With years of experience as an information technologist, I’m dedicated to helping organizations implement technology with a purpose-driven, “human-first” approach, ensuring tools like Microsoft 365 empower people to do their best work.

Teaching and knowledge-sharing are at the heart of what I do. Whether it’s through volunteering in the Microsoft Community, speaking at events, or writing as the “Joy of SharePoint,” I’m passionate about helping others unlock their potential with modern workplace solutions.
Im also a cohost of the Guardians of M365 Governance podcast, where I explore the challenges and rewards of governance, and a columnist for She is Tulsa, a quarterly magazine celebrating impactful stories from my local community.

Outside of work, you’ll often find me enjoying live music or discovering new spots in Tulsa, Oklahoma, combining my love of connection and creativity wherever I go.

Show Notes

About the sponsors

 

trustedtechteam.com TrustedTech is a leading Microsoft Cloud Solution Provider (CSP) specializing in Microsoft Cloud services, Microsoft perpetual licensing, and Microsoft Support Services for medium and enterprise-sized businesses. Our robust team of in-house, U.S-based Microsoft architects and engineers are certified in all 6/6 Microsoft Solutions Partner Designations in the Microsoft Cloud Partner Program.

ShareGate.com Your migration and governance solution for Microsoft 365
ShareGate helps your teams simplify tenant migrations, get Copilot-ready, and take control of Microsoft 365 governance.
Intelligink.com Logo Our Microsoft 365 experts and Microsoft Azure experts focus on the Microsoft cloud, so you can focus on what you do best! Learn more how we can help you!




Download audio: https://dts.podtrac.com/redirect.mp3/media.blubrry.com/msclouditpropodcast/content.blubrry.com/msclouditpropodcast/E425.mp3
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All the agents all at once

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From: kayla.cinnamon
Duration: 1:11
Views: 228

Fleets on fleets in Copilot CLI 🚀

Links:
GitHub Copilot CLI: https://github.com/features/copilot/cli/

Socials:
👩‍💻 GitHub: https://github.com/cinnamon-msft
🐤 X: https://x.com/cinnamon_msft
📸 Instagram: https://www.instagram.com/kaylacinnamon/
🎥: TikTok: https://www.tiktok.com/@kaylacinnamon
🦋 Bluesky: https://bsky.app/profile/kaylacinnamon.bsky.social
🐘 Mastodon: https://hachyderm.io/@cinnamon

Disclaimer: I've created everything on my channel in my free time. Nothing is officially affiliated or endorsed by Microsoft in any way. Opinions and views are my own! 🩷

#github #copilot #cli #ai #agents #subagents

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How to handle layoffs with compassion with Ayal Yogev, Anjuna

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This week’s guest is Ayal Yogev, co-founder and CEO of Anjuna Security, who has experienced both sides of the startup journey: scaling quickly during the boom years and then making the incredibly difficult decision to lay off a significant portion of his team when the market shifted.

From growing to 75 employees to scaling back and rebuilding, Yogev learned firsthand that the hardest part of leadership isn’t hiring fast, it’s making tough decisions with care, transparency, and integrity.

In this episode, Isabelle Johannessen and Yogev unpack what it really means to lead through layoffs with compassion and how founders can support their teams even in the most challenging moments. They also explore the lessons learned from scaling too quickly and how to build a more resilient company the second time around.

They discuss:

  • How to approach layoffs with empathy and transparency

  • Ways to support employees beyond financial compensation

  • What founders get wrong about scaling and hiring

  • Why culture matters most during difficult moments

  • Lessons from rebuilding after layoffs


Apply to Startup Battlefield: We are looking for early-stage companies that have an MVP. So nominate a founder (or yourself): techcrunch.com/apply. Be sure to say you heard about Startup Battlefield from the Build Mode podcast.  

TechCrunch Disrupt: If you're thinking about applying to Startup Battlefield, then October 13 to 15 in San Francisco, we're back for TechCrunch Disrupt, where the Startup Battlefield 200 takes the stage. So if you want to cheer them on, or just network with 1000s of founders, VCs, and tech enthusiasts, then grab your tickets.  

Use code buildmode15 for 15% off any ticket type. 

New episodes of Build Mode drop every Thursday. Hosted by Isabelle Johannessen. Produced and edited by Maggie Nye. Audience development led by Morgan Little. Special thanks to the Foundry and Cheddar video teams. 

 Chapters:

00:00 We grew too fast

02:30 What Anjuna actually does

04:45 Scaling the team quickly

06:10 The market crash hits

09:40 Handling layoffs with empathy

12:10 Supporting employees the right way

15:30 Why culture matters in crisis

20:50 The hiring mistake founders make

27:40 When to scale your sales team

34:40 Rebuilding after layoffs






Download audio: https://traffic.megaphone.fm/TCML8008837448.mp3?updated=1775750149
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Are You Using AI to Go Faster in the Wrong Direction? | Steve Pereira on Flow and Engineering

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From: Hangar DX podcast
Duration: 35:40
Views: 3

"We can be in a flow state running in the wrong direction. Unless you can tie all your actions back to your strategic imperative, you might look back in five years and think: That was fun, but could I have gotten further?"

In this episode of the HangarDX podcast, Ankit Jain, co-founder and CEO of Aviator, talks to Steve Pereira, lead consultant at Visible Value Stream Consulting and co-founder of the Flow Collective, to discuss where AI is genuinely moving the needle versus just generating more code to review, how to think about context switching and flow state when AI makes task-switching cheaper than ever, and how teams can use value stream mapping as a framework for getting AI adoption right.

00:00 Introduction to Developer Experience and Value Stream Mapping
05:20 Understanding Value Stream Mapping in Practice
08:09 The Impact of AI on Value Stream Flow
17:06 Context Switching and Flow State in Software Development
27:48 Intentionality in Context Switching and Flow State
35:07 Value Stream Mapping as a Superpower for AI Success

📫 Sign up to our email list for more podcasts, articles, events, and other updates: https://www.aviator.co/podcast

✏️ Subscribe for more videos: @Aviator-Co

🙌 Join a curated community of senior engineers and engineering leaders focused on developer experience and solving productivity challenges at scale! Check out our upcoming off-the-record online sessions where vetted, experienced professionals can exchange ideas and share hard-earned wisdom: https://dx.community/

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Claude + GPT | Multi-model intelligence in Copilot

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Generate briefing documents, presentations, and Excel files from a single prompt with Copilot Cowork, pulling from your emails, calendar, and SharePoint through Work IQ — and fold in new tasks mid-run without stopping. Using Copilot Cowork, you can use the same platform that powers Claude Cowork. It’s designed for long-running, multi-step task automation. 

Use Critique in Researcher to pair a generation model with a dedicated review model, applying source reliability and evidence grounding before the report lands. Run model Council to submit one prompt to GPT and Claude simultaneously and compare their full reasoning side-by-side. 

These experiences with Copilot Cowork and Researcher are available now if your organization has the Frontier Program enabled. Jeremy Chapman, Microsoft 365 Director, shares how to choose, direct, and compare the right AI model for every task, all from within Microsoft 365.

One prompt. Three files. 

Copilot Cowork generates your briefing doc, presentation, and Excel output — grounded in Work IQ data and saved directly to OneDrive. Try it now.

Copilot Cowork handles new requests mid-run. 

Add meeting scheduling or an email update partway through and it integrates them into the active plan. Check it out.

No more copy/paste into unmanaged AI sites. 

Work IQ automatically supplies Cowork and Researcher with your emails, calendar, Teams transcripts, and SharePoint files. Every output is grounded in your actual data. See how it works.

QUICK LINKS: 

00:00 — Copilot capabilities 

01:06 — Copilot Cowork 

02:32 — Mid-Run Task Injection 

03:05 — Output 

04:17 — Researcher Critique: Dual-Model Pipeline 

05:58 — Work IQ Auto-Retrieval 

06:58 — Model Council 

08:50 — Wrap up

Link References

Try it at https://microsoft365.com/copilot

Unfamiliar with Microsoft Mechanics? 

As Microsoft’s official video series for IT, you can watch and share valuable content and demos of current and upcoming tech from the people who build it at Microsoft. 

Keep getting this insider knowledge, join us on social: 


Video Transcript:

-Now you don’t need to switch between AI model providers for the best models for work. Copilot has options from Anthropic and OpenAI available directly from Microsoft 365. Using Copilot Cowork, you can use the same platform that powers Claude Cowork. It’s designed for long-running, multi-step task automation and it’s grounded by Work IQ, so you don’t need to move files and data outside of Microsoft 365 to other potentially unprotected services. Researcher has also been expanded with multi-model intelligence, where the new Critique capability separates the models, with one used to generate and another to refine its research outputs. And the new Council capability lets you submit a single prompt and view a side-by-side comparison across multiple model outputs. 

-Now, these experiences with Copilot Cowork and Researcher are available now if your organization has the Frontier program enabled, and today I’ll go hands-on with each while explaining the mechanics of how they work. Let’s start with Copilot Cowork. So in this example, I need to prepare for a customer meeting, and I want Cowork to build me a briefing document in Word, a PowerPoint presentation, and an Excel file with customer insights. I already have Copilot pinned with my agents and it’s opened. 

-Before I start, I’ll show you what’s set up in the knowledge sources. I can access information on the web, from people, and from Work IQ, so it doesn’t rely on connectors to access my work files, calendar, or previous meetings. Now I’ll paste in my prompt with links to reference files so it can help me then prepare for my meeting, and I want Copilot to pull in details from relevant emails and my calendar. I’ve also referenced an existing briefing document template as an example to follow, as well as an Excel overview with customer-specific metrics and visuals. And I want it to create a new briefing document as well as a client-ready PowerPoint presentation with our differentiators and recommended next steps. 

-So now I’m going to kick off the process and Cowork will show its progress, its inputs and outputs on the upper right-hand side of the screen. Cowork will then reason through all of the inputs and tasks from my prompt, then systematically work through everything until it generates the files that I requested. And it’s not only using the files referenced, but also searching across my Work IQ information. As it works, I can even request more tasks while it’s running. 

-For example, I can ask it to schedule prep time with people on my team and send an email status update to the account team. Cowork just folds that into the plan and keeps going. It checks schedules, and here’s the meeting it proposes for me and Riley on my team to review, and I’ll create that right from here. Then it authors an email to Ellis from the account team that I can choose to edit manually if I want. I’ll go ahead and add a thank you in line and then hit send. This can process for several minutes, so to save a little time, I’ll move on to when everything is complete. You’ll see that on the right in the output folder, it’s created a Zava client presentation, a customer briefing doc, and also a customer overview Excel file. 

-Now, I’ll open up the briefing document first, and it has everything relevant to the meeting and it uses our standard briefing template. In fact, if I open up the original one, you can see just how close the formatting is. Now I’ll open the presentation it generated. It explains our work at a glance, with key metrics from Work IQ and referenced files, as well as revenue and growth highlights. Now if I move on to the generated Excel file and open that, it’s laid out our year-over-year performance and used it to create forecasts for this year. We can also see the growth trends over time, and if I click into Sales by Category, we can even see a detailed breakdown across different product lines with comparisons for the last two years. And as it worked on my behalf, everything was saved directly into OneDrive, so it’s protected and can be shared with my team like any other Microsoft 365 file. 

-Next, one of the most powerful experiences in Copilot, Researcher, has also added new multi-model intelligence capabilities in addition to its options for using Claude from Anthropic or GPT from OpenAI. Researcher now takes us a step further with Critique by using a combination of models to separate generation from evaluation tasks, where one model leads the generation phase, planning the task, iterating through retrieval steps, and producing an initial draft, while the second model then focuses on review and refinement, acting like an expert reviewer before the final report is presented to you. This is now the default experience, and having these models work together helps ensure higher-quality outputs. Let me show you. 

-From Copilot and Microsoft 365, I already have Researcher open. At the top right, I’ll expand the model picker and explain the options. Choosing Auto will automatically generate responses using Critique with the two models working together. Under that is an option for Model Council that I’ll walk through in a moment. Then there are also options to choose GPT and Claude as standalone models. So I’m going to keep Auto in this case, and then I’ll paste in my prompt to generate an executive brief about the competition in our industry and where there might be expansion opportunities. Now, this is a very research-intensive request that will need to retrieve, evaluate, and analyze many resources via Work IQ and the web. 

-Now I’ll submit my prompt to get it started. Researcher can take several minutes to research and reason over a topic and generate its response, so to save a little time, I’ll move to its output. On the top I can see the content was generated by GPT and refined by Claude. First, there’s an executive summary about the market-related conditions. As I scroll down, you can see it’s assessed source reliability, where it focuses on reputable, authoritative, and domain-appropriate sources. Then as I continue scrolling, it’s also assessed report completeness, where the reviewer model ensures that the final report satisfies the request, along with relevant insights. 

-As you can see with the rest of the citations, it’s enforced strict evidence grounding, making sure that every key claim is anchored to a reliable source. So for example, here you can see that it’s pulled in structured data from an Excel file with detailed financials and several relevant Word documents from our internal SharePoint sites. And it’s done all of this research automatically without me having to manually reference or upload files into my prompt. Both models work together in this case to improve the generated output. Next, let’s move on to Model Council in Researcher. Now, this lets you compare responses from different models side by side so that you can see where they agree, where they don’t, as well as what differentiates each model. 

-So I’m back in Researcher, and this time from the model picker, I’ll choose Model Council. From there, I’ll just paste in my detailed prompt, in this case to review our latest customer feedback interviews to find the top themes and give recommendations based on our current plans in motion. Again, this is going to leverage Work IQ to find and analyze recent Teams meeting transcripts, our product plans from files and SharePoint and more as research sources, and it’s a lot to process. Everything looks good here, so I’ll go ahead and send it. And in this case, Researcher asks clarifying questions to better understand my goal. 

-So I’ll choose a short one-to-five-page report length. Then below that I’ll type “Go ahead” and it gets to work. I only need to submit my prompt one time for both models to process it simultaneously. Again, this process can run 10 or more minutes, so I’ll skip to the output. You can see that each model has its own tile on top, and you can click into any of them to view their outputs. Below that is a summary for how each model did, comparing their responses. And I can also view a full output for each model. So I’m going to drill into the GPT output, and that shows me a split-screen view with the GPT tab open on the right, and I can scroll its results and I can look at its structured reasoning and its response and all the details. 

-Now moving to the Claude tab, I can also look at its detailed response and reasoning and everything that it performed to derive the output. I don’t need to run separate prompts to find the model that I prefer. Now Model Council helps do that work for me. So now Copilot and Microsoft 365 gives you direct access to leading models, including Anthropic and OpenAI, with multi-model intelligence and without having to switch between platforms. 

-To get started, enable the Frontier program in your Microsoft 365 environment. Then go to microsoft365.com/copilot or use the mobile app to try it out. And keep watching Microsoft Mechanics for the latest tech updates, and thanks so much for watching.

 

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