The big deal: this isn’t a lab demo. MedOS just deployed inside Stanford Blood Center and Stanford Pathology, and it’s being presented at NVIDIA GTC: the same conference where most of the modern AI stack gets unveiled. If it works, this is the first real glimpse of AI-native
ENTERPRISE AI
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AI Copilots Revolutionize Medicine with MedOS: ChatGPT, XR Glasses, and Robotic Hands for Doctors
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AI copilots are coming for medicine.
— AI Breakfast (@AiBreakfast) 14 mars 2026
MedOS is basically ChatGPT + smart glasses + robotic hands for doctors.
A physician can wear XR glasses, see a patient, and the system:
• watches the procedure in real time
• reasons with multi-agent AI models
• suggests diagnoses or… pic.twitter.com/PbxnYVO227AI copilots are coming for medicine. MedOS is basically ChatGPT + smart glasses + robotic hands for doctors. A physician can wear XR glasses, see a patient, and the system: • watches the procedure in real time
• reasons with multi-agent AI models
• suggests diagnoses or -
Claude Code and AI Agents Replacing Entire Engineering Organizations
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To expand, this would entail Claude Code (or other) generating data pipelines, data, models, training schemes, etc. ie the code agent recreates not only a SWE, but the whole of the organisation’s work over the last few years. I don’t believe access to data or compute are walls
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How to use a prompt for business problem solving
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How to use it: 1. Copy the full prompt
2. Fill in the 5 fields at the bottom with your specific situation
3. Run it in Claude, ChatGPT, or Grok Works for pricing wars, team dysfunction, retention loops, scaling bottlenecks, or any problem where fixing one thing keeps breaking -
Databricks Certifications Drive Career Growth in Data and AI
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In data and AI, validated expertise is becoming a real differentiator — for career growth, credibility, and visibility. Professionals with Databricks certifications report tangible outcomes: promotions, expanded opportunities, stronger credibility in leadership discussions, and
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Agentic RAG: The 9-Layer Stack for Production AI Systems
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Agentic RAG = 9-layer stack Infra → Eval → Models → Orchestration
→ Vector DB → Embeddings → Ingestion
→ Memory → Safety RAG alone isn’t enough.
Add planning, memory, governance. That’s production AI. #AgenticAI #RAG #LLM #AIStack -
Claude Code Generating Claude Code: Anthropic’s Future Implications
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What happens to Anthropic when anyone can use Claude Code to generate Claude Code?
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Enterprise MCP Version with Custom Support Available
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Nice! If you want the enterprise version of this with support for all the custom mcp – reach out @MintMCP_AI
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Securing Long-Running Self-Evolving AI Agents: Infrastructure Panel
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How do you secure long-running self evolving agents?
— NVIDIA AI (@NVIDIAAI) 14 mars 2026
Join our panel at #NVIDIAGTC featuring @CrowdStrike, @ServiceNow, and other industry leaders to learn about the infrastructure required to govern self-evolving AI agents like @OpenClaw.
📅 Monday, March 16 | 3:00 PM – 4:00… pic.twitter.com/evhPvV2faMHow do you secure long-running self evolving agents? Join our panel at #NVIDIAGTC featuring @CrowdStrike
, @ServiceNow
, and other industry leaders to learn about the infrastructure required to govern self-evolving AI agents like @OpenClaw
. Monday, March 16 | 3:00 PM – 4:00 -
AI Vision, LLMs, Programming: Factory Stack Integration 2026
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AI Vision. Large Language Models. AI Programming. All three are being prioritized together by manufacturers in 2026. They are not competing for the same budget. They are components of the same software-defined factory stack, each amplifying the others.