At #MWC2026, Huawei and its customers released 115 industrial intelligence showcases, demonstrating how AI and digital infrastructure are being applied in real operational environments. My latest article explores key insights from the Industrial Digital and Intelligent
@ingliguori
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Agentic RAG: AI Evolution from Reasoning to Action
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AI is evolving fast. From retrieval → to reasoning → to action. That’s **Agentic RAG** 5 building blocks: 1. AI Agents
2. LLMs
3. Knowledge layers
4. APIs
5. Execution systems The result? AI that doesn’t just answer AI that actually *does* This is where real ROI -
Huawei Showcases 115 Industrial AI Solutions at MWC2026
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At #MWC2026, Huawei and its customers released 115 industrial intelligence showcases, demonstrating how AI and digital infrastructure are being applied in real operational environments. My latest article explores key insights from the Industrial Digital and Intelligent
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Five Essentials for Responsible and Trustworthy AI
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AI without trust = risk. AI with trust = scale 5 essentials for responsible AI: Governance Anonymization Data minimization Audits Privacy by design The winners in AI won’t just be the fastest. They’ll be the most trusted. #AI #Privacy #ResponsibleAI #Tech
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Agentic AI: Beyond Intelligence to Execution
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Agentic AI = more than intelligence • Proactive decisions
• Goal-driven actions
• Context awareness
• Real-time learning
• Human collaboration
• Resource optimization
• Scalability
• Ethics It’s not about answers anymore.
It’s about execution. #AgenticAI #AI -
Top 1% LLM Users: Advanced Strategies Beyond Chatbots
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99% of people use LLMs like Google.
That’s why they get average results.
The top 1% do this instead: → Build context
→ Force reasoning
→ Iterate, don’t restart
→ Design workflows (not prompts)
→ Optimize for execution, not answers LLMs aren’t chatbots.
They’re systems.
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Essential Cybersecurity Documentation: Process Templates Across Domains
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Cybersecurity scales with process + templates Key docs every org needs: InfoSec: incident logs, access matrix, data classification Network: DDoS plan, VPN/NAC logs, patch schedule Cloud: config baseline, IR log, backup testing, asset inventory AppSec: secure
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Three AI Types Explained: From Prediction to Agentic Intelligence
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Simple way to explain AI types Traditional AI = predict/classify/detect anomalies Generative AI = create content + automate knowledge work (incl. RAG) Agentic AI = agents that use tools/APIs + orchestrate tasks end-to-end We’re moving from predict → create →
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Five Levels of AI Agents: From Rules to Superintelligence
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AI agents have levels 1. Rule-based (if-then automation) 2. Tool-using assistants 3. Strategic multi-step agents 4. Context-aware autonomous agents 5. Superintelligent digital personas (theoretical AGI) We’re moving from “AI that responds” → to “AI that executes
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AI Agents as Complete Tech Stacks Beyond LLMs
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AI agents = full tech stacks, not just LLMs. Above water: UI + “smart” assistant.
Below water: models orchestration memory/RAG tools & APIs AgentOps/observability auth & security data + ETL infra Great agents are systems + governance + data, not