R Systems

Plot twist: one trying to do everything is pure chaos. 👀⚡

Modern AI systems are evolving fast, and the way tasks are handled behind the scenes is getting far more interesting than a single prompt-response flow. 🤖

This week’s Friday AI Quiz dives into the world of multi-agent systems and intelligent orchestration. Think you know the answer? Leave it in the comments below 👇

As enterprises scale adoption, one challenge remains consistent: ensuring LLMs produce accurate, context-aware outputs. This is where context engineering and Model Context Protocol (MCP) are becoming game changers. Using servers, engineers can automatically append relevant logs, APIs, databases, files, and internal knowledge directly into prompts. The result is leaner prompts, fewer hallucinations, and significantly more relevant AI responses.

As Neeraj Abhyankar, VP of Data & AI at RSI, explains with @ InfoWorld : “MCP allows systems to dynamically fetch what the model needs. This makes prompts leaner, reduces hallucinations, and ensures models operate with task-relevant context.”

Check out the full article here: https://bit.ly/4f9v3Xy

The question for financial institutions has shifted. It's no longer "are we secure?" but rather "how fast can we know where we're exposed?"

Dataquest India's latest feature on Anthropic's Claude Mythos tackles this head-on, with our very own Rohan Gupta, VP Cloud, Security & DevOps at , contributing a sharp perspective.

Worth a full read for anyone working at the intersection of AI, cybersecurity, and financial services: https://www.dqindia.com/features/claude-mythos-and-the-cyber-resilience-question-banks-can-no-longer-avoid-11861015