ai-academy

Orchestrate data collection from Slack, Granola, GitHub, and Notion to curate AI speaker pipelines.

Updated Aug 27, 2026

Search Tags:#curation #ai #session management #knowledge sharing #speaker pipeline #org intelligence

Ready to run

npx skills add https://github.com/lzlatkin/dots --skill ai-academy

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: ai-academy
Source: https://github.com/lzlatkin/dots/tree/main/agents/skills/ai-academy
Command: npx skills add https://github.com/lzlatkin/dots --skill ai-academy

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill streamlines the process of identifying and tracking individuals within the organization who are engaged in interesting AI work, ensuring a consistent flow of speakers and relevant topics for the AI Academy sessions.

Core Features & Use Cases

Automated Discovery: Scans multiple data sources (Slack, Granola, GitHub, Notion) to identify AI-related activities and individuals.
Pipeline Management: Maintains a curated list of potential speakers and session topics, categorized by readiness and type.
Use Case: Automatically identify engineers building new AI workflows, track their progress, and suggest them as speakers for the weekly AI Academy demo session, ensuring the content remains fresh and relevant.

Quick Start

Run the ai-academy skill to perform a full sweep of all data sources and update the speaker pipeline.

Frequently Asked Questions about ai-academy

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I curate AI talent and topics for internal knowledge-sharing sessions?▼

Curate AI talent and topics by orchestrating data collection from Slack, GitHub, Notion, and Granola to identify individuals engaged in AI work and suggest them as speakers for sessions. This maintains a consistent flow of relevant internal knowledge-sharing content.

What is the best way to track potential speakers across multiple data sources?▼

Track potential speakers across multiple data sources by running automated discovery sweeps that scan Slack, Granola, GitHub, and Notion for AI activities. The skill manages persistent state for speaker tracking, activity logs, and adoption maps to maintain a curated pipeline.

Can I manage a speaker pipeline and track session readiness automatically?▼

Manage a speaker pipeline and track session readiness automatically through pipeline management features that maintain a curated list of potential speakers and session topics. Entries are categorized by readiness and type to support weekly knowledge-sharing events.

Does the speaker discovery process work with Slack, Notion, and GitHub?▼

Speaker discovery works with Slack, Notion, GitHub, and Granola by scanning these data sources to identify AI-related activities and individuals. It supports both scheduled sweeps for comprehensive updates and quick syncs for immediate checks.

How do I identify engineers building new AI workflows for demo sessions?▼

Identify engineers building new AI workflows by scanning organizational data sources for AI-related activities and tracking their progress. The skill automatically suggests these engineers as speakers for weekly AI Academy demo sessions to keep content fresh.

What are the limitations of using automated discovery for session topic curation?▼

Automated discovery for session topic curation relies on scanning existing data sources like Slack, GitHub, Notion, and Granola, so its limitations include dependency on the activity levels within those platforms and the need for persistent state management to avoid duplicate speaker suggestions.