Kamya Shah

Kamya Shah

Ensuring AI Agent Reliability in Production Environments: Strategies and Solutions

Ensuring AI Agent Reliability in Production Environments: Strategies and Solutions

TL;DR AI agent deployments face significant reliability challenges, with industry reports indicating that 70-85% of AI initiatives fail to meet expected outcomes. Production environments introduce complexities such as non-deterministic behavior, multi-agent orchestration failures, and silent quality degradation that traditional monitoring tools cannot detect. Organizations need comprehensive strategies combining agent
Kamya Shah
Building a Robust Evaluation Framework for LLMs and AI Agents

Building a Robust Evaluation Framework for LLMs and AI Agents

TL;DR Production-ready LLM applications require comprehensive evaluation frameworks combining automated assessments, human feedback, and continuous monitoring. Key components include clear evaluation objectives, appropriate metrics across performance and safety dimensions, multi-stage testing pipelines, and robust data management. This structured approach enables teams to identify issues early, optimize agent behavior systematically,
Kamya Shah