Kuldeep Paul

Kuldeep Paul

Agentic AI | LLM | Product Management | Product Marketing | Data Science | SaaS

Top 5 Prompt Management Platforms in 2025: A Comprehensive Guide for AI Teams

Top 5 Prompt Management Platforms in 2025: A Comprehensive Guide for AI Teams

Managing prompts effectively has become a critical challenge as organizations scale their AI applications. According to recent research, prompt engineering accounts for 30-40% of the time spent in AI application development, making dedicated prompt management infrastructure essential for enterprise AI teams. Prompt management platforms provide centralized systems for versioning, testing,

Top 3 AI Evals Tools for Enterprises in 2025: Features, Strengths, and Use Cases

Top 3 AI Evals Tools for Enterprises in 2025: Features, Strengths, and Use Cases

TL;DR: Enterprise AI evaluation must cover three layers end to end: experiment, evaluate, and observe. Choose a platform that unifies offline evals, agent simulations, and online evals in production, and integrates with your observability stack. Priorities for 2025 include OpenTelemetry compatibility, human-in-the-loop pipelines, dataset curation from production logs, and

Top 3 AI Evaluation Tools in 2025: Comparison between Maxim AI, Arize, and Langfuse

Top 3 AI Evaluation Tools in 2025: Comparison between Maxim AI, Arize, and Langfuse

As AI agents are becoming more mainstream and have started powering mission-critical business workflows, evaluating your AI Agents has become imperative. In 2025, the landscape of AI evaluation tools has matured rapidly, offering teams not just basic benchmarking but comprehensive observability, simulation, and evaluations to test their AI applications end-to-end.

Top 3 AI Testing Platforms in 2025: Comparison between Maxim AI, Langfuse and Braintrust

Top 3 AI Testing Platforms in 2025: Comparison between Maxim AI, Langfuse, and Braintrust

TL;DR Advanced AI models currently solve less than 2% of problems in FrontierMath, a benchmark designed by expert mathematicians to test research-level mathematical reasoning. This represents a significant gap between current AI capabilities and human-level mathematical expertise. As AI systems approach this milestone, organizations must prepare with robust evaluation

Improving Prompt Engineering for Enterprise AI Agents

Improving Prompt Engineering for Enterprise AI Agents

Prompt engineering has evolved from a niche technical skill to a critical competency for enterprise AI deployment. The challenge isn't just crafting the perfect prompt, it's thoughtfully curating what information enters the model's limited attention budget at each step. As organizations transition from proof-of-concept

A/B Testing Strategies for AI Agents: How to Optimize Performance and Quality

A/B Testing Strategies for AI Agents: How to Optimize Performance and Quality

A/B testing has evolved from a simple website optimization technique to a critical methodology for evaluating and improving AI agent performance. As enterprises deploy increasingly sophisticated agentic AI systems, traditional testing approaches often fall short. AI agents are transforming A/B testing from a blunt instrument into a precision

Building Multi-Agent AI Systems: A Deep Dive into Agent Collaboration and Communication

Building Multi-Agent AI Systems: A Deep Dive into Agent Collaboration and Communication

Introduction The evolution of artificial intelligence has moved beyond single-agent architectures into sophisticated multi-agent systems that can decompose complex tasks, collaborate effectively, and achieve outcomes that individual agents struggle to accomplish. While single AI agents powered by large language models have demonstrated remarkable capabilities, they often hit limitations when tackling