ai

An Agent Mesh Architecture for Treasury and Liquidity Management (TLM) with source code on Github. https://github.com/chrisshayan/agentic-tlm

This article unveils a sophisticated AI architecture featuring 12 specialized agents working in concert, powered by LangGraph, RAG, and multi-modal AI, to dissect financial data, predict outcomes, and automate complex underwriting tasks.

Imagine every employee having their own personalized culture coach !!!

The lending landscape is clearly evolving, and I've been considering how Agentic AI, particularly when orchestrated with LangGraph, might offer new possibilities for Loan Origination Systems.

My latest article, "Know Your Data" breaks down zero-party, first-party, second-party, and third-party data, and explores how a Customer Data Platform (CDP) can integrate them for maximum impact.

A fascinating discussion with Lan Doan about her innovative use of AI in coaching and the thought-provoking HBR article “Want to Use AI as a Career Coach? Use These Prompts” by Tomas Chamorro-Premuzic have ignited a particular interest in me.

My latest blog post goes deep into the crucial role of ontologies in driving Explainable AI (XAI).

Don't just predict – understand and influence!

This article breaks down how to build an Agentic RAG system using LangChain, LangGraph, Cursor, MCP, and more. Get hands-on with practical code examples for AST parsing, vector database integration, and IDE plugins.