AI tool usage at scale is here. ChatGPT: 4.7B monthly visits (Jan 2025)
Canva: 887M
Google Translate: 595M
DeepSeek: 268M (massive surge) http://
Character.AI: 226M
Perplexity: 133M
Gemini: 118M
Claude: 105M AI isn’t a trend anymore — it’s infrastructure. What’s your #1
@ingliguori
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AI tool usage at scale: ChatGPT leads with 4.7B monthly visits
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Better prompts lead to better AI outputs: structure, analysis, conversation, planning.
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Better prompts = better AI outputs • Structured → precision
• Analytical → research
• Conversational → ideas
• Planning → execution Great prompts are frameworks, not guesses. Via Giuliano Liguori (
@ingliguori
) #AI #Prompts #GenAI -
AI Agent Development Roadmap: From LLMs to Orchestration
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The roadmap to building AI agents is becoming clearer Learn LLMs & prompting Add tools & APIs Implement memory Build workflows Orchestrate multi-agent systems Deploy, monitor, improve Great agents are not just intelligent.
They are connected, stateful, -
Claude Features Enable AI Integration into Real Workflows
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Claude is more than a chatbot • Projects → persistent context
• Artifacts → live outputs
• MCP → external tools
• Connectors → enterprise knowledge
• Rules → operational consistency AI becomes powerful when connected to real workflows. Via Giuliano Liguori -
AI Agents for Small Business Automation with n8n
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AI agents for small business • Automate leads
• Automate email
• Automate support
• Connect workflows
• Reduce manual work AI + n8n = scalable automation without complex coding. Via Giuliano Liguori (
@ingliguori
) #AI #Automation #n8n -
AI Agents Beyond LLMs: Orchestration and Architecture
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AI agents are more than LLMs • Skills → expertise
• MCP → external connections
• Subagents → delegated tasks
• Hooks → automation
• Memory → persistent context Real AI systems are orchestration layers. Via Giuliano Liguori (
@ingliguori
) #AI #AIAgents #MCP -
τ Scaling: Beyond Transistor Shrinking for AI Systems
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The proposed “τ Scaling” approach moves beyond traditional transistor shrinking and focuses more on reducing latency and improving efficiency across chips, interconnects, and AI systems. Concepts like LogicFolding, hybrid bonding, Unified Bus, and advanced system-level
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Huawei τ Scaling: Beyond Transistor Shrinking for AI
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Interesting direction from Huawei at ISCAS 2026. The proposed “τ Scaling” approach moves beyond traditional transistor shrinking and focuses more on reducing latency and improving efficiency across chips, interconnects, and AI systems. Concepts like LogicFolding, hybrid
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Scaling AI Operations Through Governance and Workflow Integration
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AI maturity is no longer about how many copilots a company has deployed. It is about whether AI can operate inside real workflows with: Identity Policy Workflow Audit The market is moving from AI pilots to AI operations. Governance is the scaling layer. The key
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The Shift from Model-Centric to Control-Plane AI
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AI maturity is no longer measured by how many copilots a company has deployed. It is measured by whether AI can operate inside real workflows with: Identity Policy Workflow Audit The market is moving from model-centric AI to control-plane AI. More demos will not