Pranay Batta

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

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

AI agents have matured from weekend hackathon curiosities into the backbone of production-grade applications. 2025’s developer toolchain is flush with frameworks that promise plug-and-play reasoning loops, deterministic tool calls, and battle-tested orchestration. Yet, despite the marketing noise, only a handful of these frameworks are truly open source, community-driven, and