Guides

 Building Production-Ready Multi-Agent Systems: Architecture Patterns and Operational Best Practices

Building Production-Ready Multi-Agent Systems: Architecture Patterns and Operational Best Practices

Multi-agent systems represent a fundamental shift in how AI applications handle complexity. When a single large language model cannot efficiently process multiple concurrent tasks, distributing work across specialized agents becomes necessary. However, this distribution introduces coordination overhead, failure dependencies, and monitoring challenges that require careful architectural planning. This guide examines
Kuldeep Paul
How to Implement Observability in Multi-Step Agentic Workflows: A Technical Guide with Code Examples

How to Implement Observability in Multi-Step Agentic Workflows: A Technical Guide with Code Examples

Introduction Observability is the backbone of reliable, scalable, and trustworthy AI systems. As AI applications evolve from simple, single-step chatbots to complex, multi-step agentic workflows (incorporating RAG pipelines, tool calls, and multi-turn conversations) the need for robust observability becomes paramount. This blog provides a comprehensive, technical walkthrough for implementing observability
Kuldeep Paul
How to build a Real-Time AI Interview Voice Agent with LiveKit and Maxim: A Technical Guide

How to build a Real-Time AI Interview Voice Agent with LiveKit and Maxim: A Technical Guide

AI-powered interview agents are rapidly transforming the recruitment landscape, enabling organizations to conduct scalable, consistent, and insightful candidate assessments. By leveraging real-time voice capabilities and advanced observability, these systems offer a glimpse into the future of automated interviewing. This guide presents a comprehensive walkthrough for building a robust AI Interview
Kuldeep Paul