From Agent-1 to Superintelligence: Decoding the AI 2027 Scenario and Its Profound Implications https://
linkedin.com/pulse/from-age
nt-1-superintelligence-decoding-ai-2027-its-giuliano-liguori–vb1vf
… via @ingliguori
@ingliguori
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From Agent-1 to Superintelligence: AI 2027 Scenario Implications
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From Agent-1 to Superintelligence: AI 2027 Scenario Implications
By
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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 -
Complete Roadmap to Master Agentic AI Development
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Roadmap to learn Agentic AI AI fundamentals
Python + frameworks
LLMs
Agents architecture
Memory + RAG
Planning & decision-making
RL & self-improvement
Deployment
Real-world automation
Agentic AI = full-stack intelligence.
Credit: Tiksly
#AgenticAI #LLM #RAG #A -
Agentic AI Periodic Table: From LLM to Autonomous Systems
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Agentic AI now has its own “Periodic Table” From: LLM, RAG, RL
to PLAN, MAS, LTM
to SAFE, HUMAN oversight
to HR, MKT, LEGAL use cases
Autonomous AI = memory + planning + tools + safety + collaboration.
It’s a system, not a prompt.
Credit: Prem Natarajan
#AgenticAI #AIStack -
Agentic AI: From Generation to Autonomous Orchestrated Systems
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Agentic AI = layered intelligence.
AI/ML → Deep Learning → GenAI → AI Agents → Agentic AI.
From: • Data → Decisions
to
• Content → Tasks
to
• Autonomous, governed systems.
The future isn’t just generation.
It’s orchestration + memory + planning + safety.
That’s the real -
Five Pillars of Modern AI: From Answers to Execution
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Modern AI = 5 pillars Generative AI (create) LLMs (reason) RAG (ground + verify) AI Agents (act) Agentic AI (coordinate + scale) We’re moving from AI that answers → AI that executes outcomes. Which pillar wins next? #AI #GenerativeAI #LLMs #RAG
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Agent-1 to Superintelligence: Decoding AI 2027 Implications
By
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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 -
Agentic AI Fundamentals: Planning, Memory, Tools, and Multi-Agent Systems
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Agentic AI, simplified: • Agents are systems
• Plan → Act → Reflect loops
• Memory = compounding intelligence
• Tools = real-world impact
• Multi-agent > single-agent If it only chats, it’s not agentic. Via @ingliguori -
From Agent-1 to Superintelligence: AI 2027 Scenario Implications
By
–
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 -
9 Steps to Build Functional AI Agents from Scratch
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How to build AI agents from scratch (9 steps): 1. Purpose & scope 2. I/O schemas 3. System instructions 4. Reasoning + tools 5. Multi-agent orchestration 6. Memory & context 7. Multimodal 8. Structured outputs 9. UI / API Ship agents that do work, not just talk.