Perspectives on the decisions, assumptions, and responsibilities behind technology. Each develops a position, explains the evidence behind it, and considers where the argument may not hold.
Cloud platforms now run on specialized processors and regional AI infrastructure. This Perspective asks which investments become reliable, affordable services.
From Oracle and Meta to Microsoft and Block, technology companies are changing their investment and workforce priorities. This TechiesJournal Author Perspective examines what those decisions reveal, and what they cannot prove, about AI, productivity and human expertise.
As AI begins controlling physical machines, how do we know those machines are safe? A practical engineering Perspective on robotics, safeguards, real-world testing and emerging research in India.
How API gateways and AI gateways work, where their responsibilities differ and how to choose the right architecture.
What happens when an AI agent finds a route its operator never intended? Three documented incidents reveal the difference between solving a task and having permission to act.
AI can improve productivity and remove repetitive work. As it moves into development, operations and decision-making, organizations also need to preserve the knowledge, evaluations and architecture that allow them to adapt later.
A practical guide to free agentic-AI learning, hands-on credentials and professional certifications from major AI and cloud providers.
Learn how a simple tool-using AI agent grows into a reliable agentic system with state, evaluation, observability, security and failure handling.
Should you learn to build agentic systems? A practical learning direction for students, developers, cloud professionals and AI architects.
The Learning We Must Preserve as We Automate Work
