Pranay Batta

Pranay Batta

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

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

AI agents in 2026 commonly span tool use, retrieval, and multi-turn dialogue workflows. 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, why it

Top 5 Agent Simulation Tools in 2026: What To Use, When, and Why

Top 5 Agent Simulation Tools in 2026: What To Use, When, and Why

TL;DR: Simulate before you ship. That is the single rule every serious AI team ends up learning. Maxim AI gives you end to end simulation, evaluation, and production observability in one place. You can prototype crew patterns with CrewAI, replay and inspect chains with LangSmith, harden runs with AgentOps,

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 environments that approximate 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

Monitoring Latency and Cost in LLM Operations: Essential Metrics for Success

Monitoring Latency and Cost in LLM Operations: Essential Metrics for Success

A practitioner's guide to monitoring LLM latency and cost in production, covering trace-level observability, tail percentiles, token accounting, semantic caching, and gateway-level governance. TLDR User experience and unit economics in production AI hinge on LLM latency and cost. Effective monitoring rests on end-to-end traces,

Top MCP Gateways Optimized for Speed and Scale

Top MCP Gateways Optimized for Speed and Scale

A side-by-side look at four MCP gateways, evaluated on latency, throughput, governance, and deployment fit for production AI workloads. TLDR: MCP adoption is climbing, and so is the operational overhead of wiring tool connections together across teams and agents. This piece walks through four MCP gateway options worth

Best Tools for AI Agent Simulation in 2026: A Guide to Choosing the Right Tool for Your Use Case

Best Tools for AI Agent Simulation in 2026: A Guide to Choosing the Right Tool for Your Use Case

As AI agents support more customer interactions, operational workflows, and multi step tasks, the need for predictable and reliable behavior increases sharply. A single incorrect reasoning step, an invalid tool call, or a loop that never terminates can disrupt user experience or create compliance-related exposure. This has made AI

7 Important metrics to track for AI Agent Observability

7 Metrics You Should Track for AI Agent Observability

A practical guide to the seven core metrics for AI agent observability, covering reliability, debugging speed, cost control, and production-grade performance. TL;DR This article covers seven core metrics worth tracking for AI agent observability: Step Completion, Step Utility, Task Success, Tool Selection, Toxicity, Faithfulness, and Context Relevance, applied