Prompting is also changing. It’s no longer just “asking AI questions.” It’s becoming product design. You describe what you want.
The UI appears.
The visuals appear.
The workflow appears.
@debashis_dutta
-
Prompting evolves from questioning into product design discipline
By
–
-
Portfolio Strategy: Specialized Models Beat One-Size-Fits-All
By
–
The winning strategy is not one model to rule them all. It’s a portfolio: • reasoning models
• fast models
• research models
• coding agents
• multimodal systems
A model for every job. -
Ecosystems matter more than individual AI models
By
–
Most people are still thinking in terms of “which model is best?” That’s yesterday’s question. The new question is: Which ecosystem helps people move from idea → execution fastest?
-
AI Competitive Advantage: Workflow, Interface, Infrastructure Matter Most
By
–
Not just the model. The workflow.
The interface.
The infrastructure.
That’s where the real moat is being bui -
The Real AI War: Who Controls the Entire Stack
By
–
Everyone is arguing about ChatGPT vs Claude.
— Dr. Debashis Dutta (@debashis_dutta) 10 mars 2026
That’s not the real battle.
The real AI war is about who owns the entire stack. pic.twitter.com/Ngt3rscobsEveryone is arguing about ChatGPT vs Claude. That’s not the real battle. The real AI war is about who owns the entire stack.
-
Research initiatives in AI quantum computing and emerging technologies
By
–
Follow my work and research initiatives: Amazing AI, Data, Quantum Computing & Emerging Technologies https://
drdebashisdutta.com Research & Innovation – Quantum, AI & Advanced Systems https://
researchedge.org -
Research Collaboration in AI and Machine Learning Systems
By
–
I welcome discussions and research collaboration in: • Artificial Intelligence
• Scientific Computing
• Machine Learning Systems
• Advanced Predictive Modeling -
Data-Driven AI Modeling Accelerates Scientific Discovery
By
–
As Artificial Intelligence advances, data-driven modeling will increasingly complement traditional scientific approaches, accelerating discovery across engineering and applied sciences.
-
AI Frameworks Enhance Predictions in High-Dimensional Scientific Data
By
–
One important takeaway: AI-driven frameworks can significantly enhance predictions in high-dimensional scientific datasets where conventional analytical models struggle with nonlinear dynamics.
-
Agentic AI: Autonomy, Guardrails, and Multi-Agent Architecture
By
–
Chatbot ≠ Agentic.
— Dr. Debashis Dutta (@debashis_dutta) 14 février 2026
RPA ≠ Agentic.
RAG ≠ Agentic.
Agentic AI = orchestrator + memory + planning + tools + feedback, plus multi-agent specialists (retrieval/coding/citations).
The board question: where do we allow autonomy—and with what guardrails? pic.twitter.com/AEnajJZeEPChatbot ≠ Agentic.
RPA ≠ Agentic.
RAG ≠ Agentic. Agentic AI = orchestrator + memory + planning + tools + feedback, plus multi-agent specialists (retrieval/coding/citations). The board question: where do we allow autonomy—and with what guardrails?