Agentic AI, LLM engineering, and the models behind modern automation — multi-agent systems, LLM evaluation and comparisons, RAG, fine-tuning, AI infrastructure, security, and production AI engineering.
From the blog
Technical comparison of GPT-5.4 Mini (fast, cost-efficient, 2x faster) vs GPT-5.4 Thinking (deep reasoning) for different AI agent use cases with benchmarks and decision framework.
How IQVIA built and deployed 150+ AI agents for clinical trial site selection, regulatory compliance, and drug discovery — with enterprise architecture lessons.
How to structure AI agents as microservices with proper service boundaries, gRPC communication, circuit breakers, health checks, and service mesh integration.
Deep dive into Microsoft Agent 365 (GA May 1, 2026) and how it serves as the control plane for observing, securing, and governing AI agents at enterprise scale.
Comprehensive guide to NIST's new standards for autonomous AI systems covering security requirements, interoperability, international alignment, and practical compliance steps.
Technical analysis of NVIDIA's Vera CPU designed for agentic AI workloads — why the CPU is the bottleneck, how Vera's architecture addresses it, and what it means for agent performance.
How to build AI agents that catch and fix their own errors through output validation, reflection prompting, retry with feedback, and graceful escalation when self-correction fails.
Learn how ServiceNow's Now Assist and AI agents automate IT service management, HR service delivery, and customer service workflows with enterprise-grade reliability.
Complete testing guide for AI agents covering mocking LLM responses for unit tests, integration testing with tool calls, and end-to-end evaluation with golden datasets.
