القائمة
Real-time competitive analysis of the AI market. Covers foundation models, products, pricing, moats, and strategic positioning across major AI labs and emerging players.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
Framework for navigating AI safety, ethics, and capability trade-off discussions. Covers responsible scaling, content policy, bias, privacy, dual-use, and alignment.
Structured analytical and metrics framework for AI product roles. Covers: metrics, goal-setting, root-cause analysis, trade-offs, A/B tests.
Structured behavioral PM framework for AI product roles. Covers: leadership stories, conflict resolution, stakeholder management.
Interactive PM mock interview simulator for AI product roles. Plays the role of interviewer, asks follow-ups, scores answers against hiring rubrics, and provides detailed feedback. Supports all round types: product sense, strategy, analytical, technical, behavioral.
Generate end-to-end PM case studies from real AI product launches, pivots, and decisions. Analyzes what happened, why, what the PM likely decided, trade-offs made, and lessons learned.
Structured product sense/design framework for AI product roles. Covers: design a product, improve X, productize a capability.
استنادا إلى تصنيف SOC المهني
| name | ai-market-landscape |
| description | Real-time competitive analysis of the AI market. Covers foundation models, products, pricing, moats, and strategic positioning across major AI labs and emerging players. |
| argument-hint | [specific area or company to focus on] |
Generate a comprehensive, up-to-date analysis of the AI competitive landscape — the market context every AI PM needs.
/ai-market-landscape followed by a focus areaMap the current AI value chain:
Layer 5: Applications (ChatGPT, Perplexity, Cursor, vertical SaaS)
Layer 4: Orchestration (LangChain, agent frameworks, MCP)
Layer 3: Models (GPT-4, Claude, Gemini, Llama, Mistral)
Layer 2: Infrastructure (AWS, Azure, GCP, Together, Fireworks)
Layer 1: Compute (NVIDIA, AMD, custom chips - TPU, Trainium)
For each layer:
Compare the major model providers:
| Dimension | Lab A | Lab B | Lab C | Lab D | Lab E |
|---|---|---|---|---|---|
| Latest model | |||||
| Key capability | |||||
| Pricing (input/output per 1M tokens) | |||||
| Open vs. closed | |||||
| Primary distribution | |||||
| Enterprise strategy | |||||
| Safety approach | |||||
| Funding / valuation |
Map AI products by category:
Consumer AI:
Developer AI:
Enterprise AI:
Agents & Automation:
Analyze the key strategic questions shaping the market:
Open vs. Closed:
Consumer vs. Enterprise:
Horizontal vs. Vertical:
Agents & Autonomy:
Current market data (research the latest):
Key trends to track:
Based on the landscape, highlight:
Write as an analyst briefing — data-driven, opinionated, and actionable. Use tables for comparisons. Include specific numbers and sources. Aim for ~2500 words.
This skill is ONLY valuable with fresh data:
[linked source](url) inline for all data points.