The AI ecosystem is vast and constantly evolving. To make it easier to understand, I’ve structured AI into three layers, each representing a different level of capability and autonomy. This classification helps quickly identify where an AI tool fits and how it functions within the ecosystem. Explore AI reviews and insights based on this framework to stay ahead in the AI revolution. Follow my AI learning Journey here on github.
🔹 Layer 1 – Core AI Models (Foundation Models)
These are the base AI engines that generate raw outputs, such as text, images, or audio.
Examples: GPT-4, Claude, Stable Diffusion, Whisper
🔹 Layer 2 – AI Applications & Agents
These are AI-powered tools that use Layer 1 models but enhance them with user interfaces, workflow automation, and specific use cases.
Examples: Perplexity AI, Notion AI, MidJourney UI, ChatGPT
🔹 Layer 3 – Agentic AI & Autonomous Workflows
This is where AI moves beyond responding to inputs—it plans, executes tasks, and self-improves with minimal human intervention.
Examples: Auto-GPT, Devin AI, BabyAGI
AI & Workflows
Genres
System