Pranay Batta

Pranay Batta

Session-Level vs Node-Level Metrics: What Each Reveals About Agent Quality

Session-Level vs Node-Level Metrics: What Each Reveals About Agent Quality

Evaluating AI agents requires more than a single score. Real systems involve multi-turn interactions, tool usage, retrieval, and branching decisions. The most reliable method is to measure quality at two layers: session level and node level. Session-level metrics summarize the outcome and user experience of a complete interaction. Node-level metrics

Prompt Injection: Risks, Defenses, and How To Keep Agents On-Task

Prompt Injection: Risks, Defenses, and How To Keep Agents On-Task

AI agents are embedded in workflows across planning, tool use, retrieval, and multi-turn dialogue in 2025. Alongside this growth, one persistent risk remains: prompt injection. It is simple to attempt, hard to catch consistently, and often hides in untrusted inputs or retrieved content. This analysis explains what prompt injection is,

Agent Simulation: A Technical Guide To Evaluating AI Agents In Realistic Conditions

Agent Simulation: A Technical Guide To Evaluating AI Agents In Realistic Conditions

Agent simulation is the practice of testing AI agents in controlled but realistic environments that mirror multi-turn user interactions, tool usage, and varied personas. The purpose is to reveal failure modes and measure end-to-end quality before and after release. This guide outlines core concepts, scenario design, metrics, and workflow integration,

Agent Frameworks to Finished Product: Your Cheat Code for Shipping LLM Features Fast

Agent Frameworks to Finished Product: Your Cheat Code for Shipping LLM Features Fast

Launching an LLM feature is easy. Scaling one so it never blows your SLO, budget, or brand? That takes a plan. The smartest shortcut is to lean on battle-tested open-source frameworks for agent logic, then bolt everything to Maxim for simulation, evaluation, and observability. This guide shows how six popular

LLM Product Development: A No-Nonsense Guide to Planning, Building, and Shipping at Scale

LLM Product Development: A No-Nonsense Guide to Planning, Building, and Shipping at Scale

Large language models are past the wow phase. In 2025 the north star is business value: fewer support tickets, faster document processing, happier customers, and a lower cloud bill. This guide is a ground-up playbook for turning LLM prototypes into revenue-grade products. Whenever evaluation, simulation, or prompt iteration appears, you

Building Reliable AI Agents: How to Ensure Quality Responses Every Time

Building Reliable AI Agents: How to Ensure Quality Responses Every Time

AI agents are like new hires. If you give them a half-baked job description and never check their work, they’ll embarrass you in front of the client. Give them a clear mandate, reliable feedback loops, and the right tools, and they’ll crush deadlines while you sip coffee. In

Agent Observability: The Definitive Guide to Monitoring, Evaluating, and Perfecting Production-Grade AI Agents

Agent Observability: The Definitive Guide to Monitoring, Evaluating, and Perfecting Production-Grade AI Agents

AI agents have stormed out of research labs and into every corner of the enterprise, from customer-facing chatbots that field millions of support tickets to multi-step decision-making agents that reconcile invoices or craft marketing campaigns. Yet, as adoption accelerates, one uncomfortable truth keeps resurfacing: agents behave probabilistically. They hallucinate, drift,