Visual Studio 'Tea & Technology' Video Miniseries Starts Next Week -- Visual Studio Magazine

Visual Studio 'Tea & Technology' Video Miniseries Starts Next Week

By David Ramel
09/29/2023

Microsoft is adding to its vast trove of video developer resources with a new miniseries starting next week on the company's YouTube and Twitch channels.

Titled "2023 Visual Studio Miniseries: Tea & Technology," the seven-episode video series kicks off next Wednesday, Oct. 4, with a session featuring the company's Visual Studio extension guru, Mads Kristensen, titled "Transforming Ideas into Features."

The goal of the miniseries is to provide an insider's snapshot look at some of the people who contribute to shaping the Visual Studio IDE every day.

The series is filmed at the Redmond, Wash., campus and led by podcaster Richard Campbell from .NET Rocks.

As for the "Tea & Technology" name, the company said: "Much like a cup of tea fosters rich conversations, this miniseries aims to blend tech insights with meaningful dialogue. Richard Campbell, our pro host, will fuel the conversation with a medley of coding tips, sneak peeks at upcoming features, and an exploration of what the future holds for .NET and Visual Studio."

**[Click on image for larger view.]** 2023 Visual Studio Miniseries: Tea & Technology *(source: Microsoft).*

The summary for the first episode reads: "Join veteran Principal Product Manager Mads Kristensen as he delves into the transformative journey of Visual Studio. Renowned for his extensive contributions to extensions, Mads explores how the IDE has evolved to become a comprehensive, all-in-one platform. From the power of community-driven features to the adaptability of the IDE in both individual and enterprise settings, this episode offers a sweeping view of Visual Studio's enduring appeal."

The videos hosted on YouTube and Twitch are mostly pretty short, ranging from 10 minutes to 27 minutes.

Other episodes include:

Elevating the Inner-Loop Experience -- Anthony Cangialosi, Principal Product Manager
Mastering the Debugging Game -- Leslie Richardson, Sr. Product Manager
Creating Mobile Apps with Visual Studio -- James Montemagno, Principal Manager, Tech PM
Pushing the boundaries of coding with GitHub Copilot -- Mark Wilson-Thomas, Principal Product Manager
Visual Studio & .NET: A Symbiotic Relationship -- David Fowler, Distinguished Engineer
Developer Efficiency, AI Assistance & Microsoft Dev Box -- Amanda Silver, CVP Developer Division

"We're incredibly excited to share this series with you and can't wait for you to join us on this tech-filled journey," said Jim Harrer, senior product marketing manager, Visual Studio in an announcement post this week. "Check out the episode guide above and comment below to let me know which episodes have caught your eye. Your feedback is always valuable to us."

Other video developer resources, such as the old Channel9 series, are available at Microsoft's Learn site.

About the Author

David Ramel is an editor and writer for Converge360.

Printable Format

comments powered by Disqus

Featured

Microsoft Ships Stable Versions of OpenAI Libraries for .NET and Azure

Further leveraging the relationship that vaulted Microsoft and OpenAI into leadership positions in the AI era, Microsoft this week announced stable versions of two new OpenAI libraries.
Microsoft Further Embraces OpenAPI Spec (formerly Swagger)

Microsoft has long embraced the OpenAPI Specification (formerly known as Swagger) for describing APIs, and it's now taking that support to the next level with a new online resource.
Get Good at DevOps: Feature Flag Deployments with ASP.NET WebAPI

They provide developers with the ability to toggle features on and off without having to redeploy code, making it easier to manage risk, test features in production, and facilitate smoother releases.
Implementing k-NN Classification Using C#

Dr. James McCaffrey of Microsoft Research presents a full demo of k-nearest neighbors classification on mixed numeric and categorical data. Compared to other classification techniques, k-NN is easy to implement, supports numeric and categorical predictor variables, and is highly interpretable.