AI isn’t one thing — it’s a stack. Rules → ML → Neural Nets → Deep Learning → GenAI → Agentic AI Agents don’t replace the layers below.
They orchestrate them. If GenAI answers,
Agentic AI executes.
@ingliguori
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AI as a Stack: From Rules to Agentic Intelligence
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Agentic AI: The Future of Autonomous Intelligent Systems
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Agentic AI Explained: The Future of Autonomous AI Systems in Business & Technology https://
go.kenovy.com/7ay5 What if AI could set its own goals and make independent decisions — just like a human? Agentic AI represents the next evolution of artificial intelligence, moving -
RAG is an Ecosystem, Not a Single Tool
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This is one of the cleanest visual summaries of a production-grade RAG (Retrieval-Augmented Generation) stack I’ve seen. What it highlights clearly is an often-ignored reality:
RAG is not a single tool — it’s an ecosystem. A solid RAG system spans multiple, interchangeable -
No Best AI: Orchestrate Multiple Models for Success
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There’s no “best” AI. ChatGPT = generalist
Gemini = Google-native workflows
Claude = deep reasoning & long docs
Grok = real-time social insight
Perplexity = cited research Winners don’t pick one.
They orchestrate all. -
Mental Models of AI: From Prediction to Execution
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Best mental model for AI Traditional AI → predicts
Generative AI → creates
Agentic AI → executes The jump from GenAI to Agentic AI isn’t smarter text.
It’s ownership of workflows. -
RAG as a Control Layer: Beyond Simple Search and GPT
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RAG isn’t “search + GPT”. It’s a control layer:
• limits hallucinations
• enforces evidence
• defines what the model is allowed to know LLMs generate text.
RAG defines truth. -
Agentic AI: From Tools to Systems Thinking
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AI-ready ≠ tool-ready. This cheatsheet shows the real shift:
Models → Systems
Prompts → Planning
Outputs → Outcomes Agentic AI rewards systems thinkers — not tool collectors. -
Les 4 boucles fondamentales de l’IA autonome
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Agentic AI isn’t about learning 10 steps. It’s about mastering 4 loops:
Perception → Memory → Planning → Action. Frameworks change.
Autonomy principles don’t. Build agents that think in systems, not prompts. -
AI in Education: Systems Over Tools for Better Teaching
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AI for teachers isn’t about tools. It’s about systems:
Goals → Prompts → Activities → Feedback → Reflection. When AI is designed into pedagogy,
teachers spend less time grading
and more time teaching. That’s the real upgrade. -
Agent-1 to Superintelligence: AI 2027 Scenario Implications
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From Agent-1 to Superintelligence: Decoding the AI 2027 Scenario and Its Profound Implications Check out my article: https://
linkedin.com/pulse/from-age
nt-1-superintelligence-decoding-ai-2027-its-giuliano-liguori–vb1vf
… Via @ingliguori #AI2027 #FutureTech