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Numeric Tic-Tac-Toe

Summary

Numeric Tic-Tac-Toe is a strategic variant of the classic Tic-Tac-Toe game that replaces traditional X's and O's with numbers. This mathematical twist on the timeless game was developed to add a layer of numerical strategy and mental arithmetic to the familiar 3x3 grid format.

The game originated as an educational tool to help students practice basic arithmetic while engaging in strategic thinking. Unlike traditional Tic-Tac-Toe where the objective is simply to get three symbols in a row, Numeric Tic-Tac-Toe introduces mathematical constraints that require players to think several moves ahead while considering numerical relationships.

Rules

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.NET Developer Tools Experience

🧠 .NET Analyzers

What it does:

Identifies .NET guideline and pattern violations in both generated and custom code.

Responsible:

• Arthur
• Jesse

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Creating an Azure library for .NET: Where does it hurt?

Client TypeSpec (client.tsp) errors

The TypeSpec tooling is focused on the core TypeSpec language, ensuring that the specification is syntactically valid and well-formed. However, despite the client.tsp being a critical component of Azure library generation, it lacks the same level of validation and analysis.

Challenges

• TypeSpec authors do not have advance warning or insight when the client.tsp is malformed or contains an error that makes it invalid.

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Azure SDK for .NET Code Generation Agent

Executive summary

As the Azure SDK team’s role has evolved from authoring client libraries to building tools and processes that empower Azure service teams, delivering a polished, consistent developer experience has become increasingly important.

Today, code generation sits at the heart of our strategy, yet the current tooling presents significant challenges outside of the golden path. Specifically, there is a disconnect between TypeSpec—our abstract service contract definition—and the idiomatic .NET code we aim to produce. While the generator handles simple conversions automatically, more complex scenarios often lead to confusing failures that block key steps like generating an API View for architectural review.

To address this, we propose building an integrated set of tools that:

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Leveraging AI-driven support automation for the Azure SDK repositories

Executive summary

The Azure SDK GitHub repository experiences recurring support challenges, notably repetitive customer inquiries and inconsistent responsiveness across internal teams. Users submit issues already addressed in documentation or previously resolved issues, contributing to longer response times and unnecessary workloads. Additionally, engagement levels vary significantly among the teams responsible for different Azure SDK packages, leading to uneven customer experiences.

We propose implementing AI-driven support automation to streamline issue management and improve customer satisfaction. This solution will reduce time-to-resolution, deliver a consistent support experience, and enable engineering teams to focus on high-impact development efforts. Other key benefits include:

• Improved automated triage classification of incoming GitHub issues.
• Detection and intelligent response to common, previously solved questions.

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Microsoft Messaging: AMQP client library (early concept)

The high-level goal for the Microsoft Messaging client library is to provides a unified experience for core messaging scenarios needed by developers wishing to interact with Microsoft Fabric, Azure Event Grid, Azure Service Bus, and Azure Event Hubs.

Things to know before reading

• The names used in this document are intended for illustration only. Some names are not ideal and will need to be refined during discussions.

• Some details not related to the high-level messaging operations are not illustrated; the scope of this is limited to the high level shape and paradigms for the feature area.

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Event Grid: AMQP (early concept)

Things to know before reading

• The names used in this document are intended for illustration only. Some names are not ideal and will need to be refined during discussions.

• Some details not related to the high-level concept are not illustrated; the scope of this is limited to the high level shape and paradigms for the feature area.

• Fake methods are used to illustrate "something needs to happen, but the details are unimportant." As a general rule, if an operation is not directly related to one of the Event Grid types, it can likely be assumed that it is for illustration only. These methods will most often use ellipses for the parameter list, in order to help differentiate them.

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Service Bus: Batch Delete

Currently, when messages are sent to Service Bus, they can only be removed by reading/completing them or waiting for them to age-out based on the retention policy. This can often become troublesome for applications that accumulate messages in their dead-letter queue when they do not wish to process them, or for applications with messages that are not actionable after a certain age.

Historically, developers have had to write code that loops to perform destructive reads for the messages that they want to remove. While this is relatively straightforward for purge scenarios, it can be tricky to do correctly when the desire is only to remove messages older than a given point in time.

To make this scenario easier for developers, Service Bus is adding a new operation capable of deleting batches of messages and limiting them to a specific time.

Goals

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Overview

Issues in the Azure SDK repositories use a two label system in order to classify the issue and identify the responsible party. Each issue must have a "service label" (pink) and a "category label" (yellow) to be valid. It is this combination of labels that identifies which specific library an issue is for and, by extension, who should be responsible for the issue. For example, an issue tagged with Event Hubs and Client is owned by Jesse's team. An issue tagged with Event Hubs and Mgmt is owned by Arthur's team.

This constraint is built into the AI label service; if it cannot successfully predict both labels, it will return none. When performing automated triage, the rule will always have access to both tags and needs to take both into account to find the correct owner to triage the issue to. Currently, this is not how triage handles the scenario. Instead, the rule will collect the owners of both tags and consider them both owners. For example, an issue tagged with Event Hubs and

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Azure SDK: Target frameworks and polyfill packages

Problem statement

Developers using the Azure SDK on modern versions of .NET are required to download unnecessary packages that serve as polyfills for the legacy .NET framework and unsupported versions of .NET Core.

Impact

Developers are faced with longer build times, increased application size, and unnecessary network use.