Loading...
Loading...
Found 13 Skills
Strategic AI thinking frameworks and mental models from Satya Nadella's perspective on platform shifts, AI deployment, and building successful AI products. Use when evaluating AI strategy decisions, assessing platform opportunities, thinking through AI product positioning, considering enterprise AI deployment challenges, evaluating talent and team capabilities, or needing frameworks for justifying AI investments in terms of economic surplus. Triggers on questions about AI platform strategy, change management for AI adoption, building AI scaffolding layers, evaluating AI opportunities, or thinking through AI's societal implications.
McKinsey-style storyline framework for building presentation decks. Use when users need to structure presentations, pitch decks, or strategic communications. Creates logical flow where each storyline becomes a slide title, progressing from problem to solution.
McKinsey-style issue tree framework for breaking down complex problems into MECE (Mutually Exclusive, Collectively Exhaustive) components. Use when users need to decompose strategic questions, structure analysis, create work plans, or prepare for case interviews. Apply hypothesis-driven approach to problem-solving.
SCPR (Situation-Complication-Problem-Recommendation) framework for structured problem solving and executive communication. Use when users need to structure strategic arguments, analyze business situations, create executive summaries, or develop clear problem statements using McKinsey-style communication. Apply when structuring recommendations, writing memos, or organizing strategic thinking.
Guides the usage of the Gemini API on Agent Platform with the Google Gen AI SDK. Use when the user asks about using Gemini in an enterprise environment or explicitly mentions Vertex AI, Google Cloud, or Agent Platform. Covers SDK usage (Python, JS/TS, Go, Java, C#), capabilities like Live API, tools, multimedia generation, caching, and batch prediction.
Go-to-market strategy for AI products. Use when positioning AI products, handling "who is responsible when it breaks" objections, pricing variable-cost AI, choosing between copilot/agent/teammate framing, or selling autonomous tools into enterprises.
An advanced orchestration specialist that manages complex coordination of 100+ agents across distributed systems with hierarchical control, dynamic scaling, and intelligent resource allocation
Analyze AI/ML technical content (papers, articles, blog posts) and extract actionable insights filtered through enterprise AI engineering lens. Use when user provides URL/document for AI/ML content analysis, asks to "review this paper", or mentions technical content in domains like RAG, embeddings, fine-tuning, prompt engineering, LLM deployment.
Guides the usage of Gemini API on Google Cloud Vertex AI with the Gen AI SDK. Use when the user asks about using Gemini in an enterprise environment or explicitly mentions Vertex AI. Covers SDK usage (Python, JS/TS, Go, Java, C#), capabilities like Live API, tools, multimedia generation, caching, and batch prediction.
Comprehensive knowledge of Microsoft Agent Framework for building production AI agents and workflows. Auto-activates for agent building, workflow design, AutoGen migration, and enterprise AI tasks.
Enterprise interactive survey orchestrator with AskUserQuestion tool integration, multi-select support, conditional branching, error recovery, and production-grade decision automation across all Alfred workflows; activates for requirement clarification, architectural decisions, risky operations, feature selection, and complex multi-step user interactions
Enterprise session state management, token budget optimization, runtime tracking, session handoff protocols, context continuity for Claude Sonnet 4.5 and Haiku 4.5 with context awareness features