Microsoft’s Generative AI for Beginners is a 21-lesson course that teaches the concepts and coding practices needed to build generative AI applications. It is intended for people starting with generative AI, with lessons covering both explanations and code examples.
Borrowing it
Nothing to install: this file belongs to microsoft/generative-ai-for-beginners. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/microsoft/generative-ai-for-beginners/main/AGENTS.mdgit clone --depth 1 https://github.com/microsoft/generative-ai-for-beginnersWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/microsoft/generative-ai-for-beginners/agents-md)<a href="https://agentmods.dev/instructions/microsoft/generative-ai-for-beginners/agents-md"><img src="https://agentmods.dev/badge/instructions/microsoft/generative-ai-for-beginners/agents-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/microsoft/generative-ai-for-beginners/agents-md"><img src="https://agentmods.dev/badge/instructions/microsoft/generative-ai-for-beginners/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.02850 | $0.02850 |
| Opus 5.5 | $0.01140 | $0.01140 |
| Sonnet 5.5 | $0.00570 | $0.00570 |
| Haiku 4.5 | $0.00285 | $0.00285 |
Grade A, and why
generative-ai-for-beginners AGENTS.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 323 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
Project Overview
This repository contains a comprehensive 21-lesson curriculum teaching Generative AI fundamentals and application development. The course is designed for beginners and covers everything from basic concepts to building production-ready applications.
Key Technologies:
- Python 3.9+ with libraries:
openai,python-dotenv,tiktoken,azure-ai-inference,pandas,numpy,matplotlib - TypeScript/JavaScript with Node.js and libraries:
openai(Azure OpenAI via the v1 endpoint + Responses API),@azure-rest/ai-inference(Microsoft Foundry Models) - Azure OpenAI Service, OpenAI API, and Microsoft Foundry Models (GitHub Models is retiring end of July 2026)
- Jupyter Notebooks for interactive learning
- Dev Containers for consistent development environment
Repository Structure:
- 21 numbered lesson directories (00-21) containing READMEs, code examples, and assignments
- Multiple implementations: Python, TypeScript, and sometimes .NET examples
- Translations directory with 40+ language versions
- Centralized configuration via
.envfile (use.env.copyas template)
Setup Commands
Initial Repository Setup
# Clone the repository
git clone https://github.com/microsoft/generative-ai-for-beginners.git
cd generative-ai-for-beginners
# Copy environment template
cp .env.copy .env
# Edit .env with your API keys and endpoints
Python Environment Setup
# Create virtual environment
python3 -m venv venv
# Activate virtual environment
# On macOS/Linux:
source venv/bin/activate
# On Windows:
venv\Scripts\activate
# Install dependencies
pip install -r requirements.txt
Node.js/TypeScript Setup
# Install root-level dependencies (for documentation tooling)
npm install
# For individual lesson TypeScript examples, navigate to the specific lesson:
cd 06-text-generation-apps/typescript/recipe-app
npm install
Dev Container Setup (Recommended)
The repository includes a .devcontainer configuration for GitHub Codespaces or VS Code Dev Containers:
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 323 lines · 2,850 tokens per session scan A 959e848dc2e9
generative-ai-for-beginners AGENTS.md is an instructions file published in the GitHub repository microsoft/generative-ai-for-beginners (121,848 stars, last pushed today), licensed MIT. It adds 2,850 tokens to every session, about $0.0114 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other instructions, from other repositories
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
vscode copilot-instructions.md
Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).
deno copilot-instructions.md
Copilot instructions for denoland/deno, covering deno development guide for github copilot, network access, high level overview, key directories and key files to understand first.