Artificial Intelligence tools are on the rise, from writing assistants to coding helpers and automation platforms. However, many professionals struggle to compare these tools effectively.
This is where the AI Stack becomes important. Modern AI tools like ChatGPT, NotebookLM, and Antigravity serve different purposes, and understanding their roles helps in:
- Avoiding tool overload
- Building smarter workflows
- Improving productivity
- Designing AI-powered systems
Layer 1: Conversational AI (Thinking Layer)
These foundational tools assist with:
- Brainstorming
- Learning
- Problem-solving
- Idea generation
Examples: ChatGPT, Claude, Gemini
Role: Thinking partners
Layer 2: Knowledge AI (Understanding Layer)
These foundational tools assist with:
- Brainstorming
- Learning
- Problem-solving
- Idea generation
Examples: NotebookLM, Humata, Glean
Role: AI analysts
Layer 3: Creative AI (Creation Layer)
These tools generate:
- Content
- Visuals
- Designs
- Videos
Examples: Jasper, Midjourney, Runway
Role: AI creators
Layer 4: Developer AI (Build Layer)
These tools help engineers by supporting:
- Code generation
- Architecture suggestions
- Debugging
- Workflow creation
Examples: GitHub Copilot, Cursor, Antigravity
Role: AI engineers
Layer 5: Workflow AI (Execution Layer)
Here, AI shifts from thinking to action, automating:
- Tasks
- Workflows
- System connections
Examples: Zapier, Make, UiPath
Role: AI operators
The AI Stack Diagram
- Execution → Workflow AI
- Build → Developer AI
- Create → Creative AI
- Understand → Knowledge AI
- Think → Conversational AI
Srinimf 
Start Discussion