Shyam Uthaman

AI agent observability becomes useful when a run reports success and the business record says otherwise. Imagine a purchasing agent checking a supplier confirmation for 100 industrial valves. The purchase order requires delivery on October 15. The supplier offers October 22. The agent retrieves the correct PO, completes without an error and labels the confirmation

What Is an AI Agent Harness? A Business Example of How Agents Work An AI agent harness is the software around an AI model that lets it carry out a task across several steps. It supplies instructions, access to information, tools, a place to keep track of progress, and rules for checking or stopping work.

Shadow AI often starts with a reasonable work problem. Someone needs to sort customer tickets before a service review, but the approved tool cannot read the export. They paste the file into a personal AI account, get a useful answer, and move on. A manager who discovers it has two jobs: find out what data

An enterprise AI agent sounds appealing when a team is drowning in follow-ups. It can read records, compare them, prepare a next step, and sometimes act through connected systems. The useful question for a business leader is narrower: which part of a real workflow should the agent handle, and how will we know it made

AI business use cases are useful only when they connect a business problem to suitable data, a real workflow, a measurable result and a person who remains accountable. A chatbot, prediction model or AI agent is not a business case by itself. The business case is the improvement it can produce, the evidence that supports

Human in the loop means placing a person at a defined point in an AI-supported process to review evidence, make a judgment, approve an action, correct an error or stop the process. It should identify a real decision and a person with authority. Simply adding an approval button does not create meaningful human oversight. I

What is MCP? Model Context Protocol is a common way for an AI application to discover and use approved tools, data and services. It can help an assistant move beyond answering from its existing knowledge, but it does not automatically make the assistant accurate, secure or authorized to act. The easiest comparison is a standard