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Microsoft's code-first stack for building, observing, and deploying distributed .NET apps — orchestration, service discovery, and dashboards in one package.
Microsoft's official C/C++ extension for VS Code — IntelliSense, debugging, code navigation, and toolchain integration.
Microsoft's reference architecture for placing AI-powered phone calls — your bot dials out (or callers dial in) and an LLM drives the conversation.
Microsoft Research's experimental agent that operates across the browser and local filesystem in tandem — a step toward general-purpose computer-use agents.
Python bindings for Playwright — Microsoft's cross-browser end-to-end testing framework with auto-wait and tracing.
Microsoft's IDE-style autocomplete for the terminal — ports Fig completion specs into a cross-shell command-line helper.
Microsoft Research's AI-assisted visualization tool — describe the chart you want in plain English, drag fields in, and it generates the data transforms and renders the visualization.
Microsoft's toolkit for building, testing, and deploying high-quality LLM applications — visual orchestration, tracing, and prompt evaluation.
Microsoft Research's LLM-powered multi-agent persona simulation — populate scenarios with synthetic users for product research and creative brainstorming.
CLI for common Playwright actions — record browser interactions and have it generate the Playwright code that reproduces them.
Microsoft's SDK for integrating LLMs into apps with planners, memory, plugins, and orchestration across C#, Python, and Java.
Microsoft's typed superset of JavaScript that compiles to plain JavaScript, adding static types and modern language features.
Cross-browser end-to-end testing framework from Microsoft, with a single API for Chromium, Firefox, and WebKit and built-in auto-wait.
Microsoft's compatibility layer for running Linux binaries natively on Windows, with full kernel support, GUI app integration, and tight Windows interop.
The browser-based code editor that powers VS Code, packaged for embedding in web apps with syntax highlighting and IntelliSense.
Microsoft's screen-parsing model that turns UI screenshots into structured element data — the perception layer for pure-vision GUI agents.
Free, open-source code editor from Microsoft with a rich extension ecosystem, debugging, and integrated Git.
Modern terminal for Windows with tabs, Unicode/UTF-8, GPU-accelerated rendering, and support for PowerShell, WSL, and cmd.
Microsoft PowerToys Microsoft PowerToys is a collection of utilities that help you customize Windows and streamline everyday tasks. Installation · Documentation · Blog · Release notes 🔨 Utilities PowerToys includes over 30 utilities to help you customize and optimize your Windows experience: | | | | | --- | --- | --- | | Advanced Paste | Always on Top | Awake | | Color Picker | Command Not Found | Command Palette | | Crop And Lock | Environment Variables | FancyZones | | File Explorer Add-ons |
Microsoft's MCP server for Playwright. Lets agents drive a browser via tool calls.
A comprehensive multi-language framework for building, orchestrating, and deploying AI agents and multi-agent workflows. Supports both Python and .NET with features like graph-based workflows, observability, and multiple LLM providers.
A Python utility that converts various file formats (PDFs, Office documents, images, audio, HTML, etc.) into clean Markdown text optimized for AI and text analysis pipelines. Preserves document structure while making content easily consumable by LLMs.
Open-source voice AI framework that includes advanced speech recognition (ASR) for 60-minute audio transcription with speaker diarization, text-to-speech (TTS) for 90-minute multi-speaker synthesis, and real-time streaming TTS. Operates at ultra-low 7.5Hz frame rate for efficient long-form audio processing.
A framework for training and optimizing AI agents using reinforcement learning and other algorithms. Supports any agent framework with minimal code changes and enables selective optimization of multi-agent systems.
Articles
Microsoft's curated collection of prompt-engineering best practices, techniques, and benchmarks — distilled lessons from running LLMs at scale.