Example: Market Research
User Request: "Research the current state of AI coding assistants market and create a summary document in Notion"
Workflow
1. Search
code
Notion:notion-search query: "AI coding assistants market"
Found 3 relevant pages across Engineering, Strategy, and Product teamspaces.
2. Fetch & Analyze
code
Notion:notion-fetch (3x)
Extracted market size, competitive landscape, technology trends from source pages.
3. Create Documentation
code
Notion:notion-create-pages
Output (Condensed)
markdown
# AI Coding Assistants Market Research - Oct 2025 ## Executive Summary The AI coding assistant market is experiencing 150%+ YoY growth. GitHub Copilot dominates with 60% share, but specialized tools are gaining traction in specific niches. ## Key Findings ### Market Size and Growth $800M in 2024 → $2.5B projected by 2026. Developer adoption: 23% (2023) → 47% (2024). Source: <mention-page url="...">Market Trends Q3 2025</mention-page> ### Competitive Landscape - GitHub Copilot: 60% (strong IDE integration) - Cursor: 15% (rapid growth, full IDE) - Tabnine: 10% (enterprise, on-premise) - Cody: 5% (codebase-aware) - CodeWhisperer: 8% (AWS integration) Source: <mention-page url="...">AI Tools Competitive Analysis</mention-page> ### Technology Trends Key differentiators: context awareness, customization, multi-modal interfaces, code verification. Source: <mention-page url="...">Developer Tools Landscape</mention-page> ## Next Steps 1. Monitor Cursor growth and feature releases 2. Evaluate Cody's codebase-aware capabilities 3. Document enterprise security/compliance requirements 4. Track pricing trends
Key Takeaways
- •Found relevant pages across multiple teamspaces
- •Synthesized competitive, market, and technical perspectives
- •Used proper citations linking to source pages
- •Created actionable recommendations