microsoft/ai-engineering-coach

better agentic engineering

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Summary Information

Updated 19 minutes ago

Type:Plugin / ExtensionCategory(s):AI Coding Agents LLM Evals, Guardrails & Observability AI Agents & LLM Apps

Added to GitGenius on September 16th, 2026

Created on May 6th, 2026

Open Issues & Pull Requests: 41 (+0)

GitHub issues: Enabled

Number of forks: 589

Total Stargazers: 4,264 (+0)

Total Subscribers: 23 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 18.2 hours

Mean response time: 5.9 days

90th percentile: 9.4 days

Tracked items: 44

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How this project is maintained

Roughly one issue in four opened in the past year never receives a reply. 94% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. Work labelled "bug" is answered fastest, typically in about an hour, while "enhancement" waits about 32 hours. Only 44% of issues opened in the past year have been closed. Three people close 88% of everything that gets resolved.

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Issue Activity (beta)

Open issues: 32

New in 7 days: 4

Closed in 7 days: 1

Avg open age: 87 days

Stale 30+ days: 24

Stale 90+ days: 19

Recent activity

Opened in 7 days: 3

Closed in 7 days: 0

Comments in 7 days: 0

Events in 7 days: 0

Top labels

bug (22)
enhancement (15)
agentic-workflows (6)
backlog (2)
question (2)
dx (1)
good first issue (1)
performance (1)

Most active issues this week

#262 Compatibility with Antigravity - 6 events / 2 comments
#265 Community catalog always empty: scraper looks for <article>, site now serves <div> - 3 events / 1 comments
#266 Coding Moments never renders Claude Code screenshots (counted but not extracted) - 3 events / 1 comments
#269 Canvas mode can load with an empty content pane: replayed dataReady is dispatched before app.js listens - 3 events / 1 comments

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Detailed Description

AI Engineering Coach is a TypeScript project that provides guidance and tooling for building agentic systems.

The project addresses the challenge of engineering reliable and effective AI agents by offering structured approaches to agent development. It provides resources and patterns for developers working with agentic architectures, helping them navigate common pitfalls and design decisions in this emerging area.

Developers building AI agents or systems that rely on autonomous decision-making should consider this tool if they want established patterns and best practices for agentic engineering. It suits teams exploring agent-based architectures who benefit from Microsoft's perspective on how to structure and validate these systems effectively.

The project shows active development with regular updates and engagement on issues and pull requests, indicating ongoing refinement of its guidance and tooling based on practical experience.