AgentBench

A deep-dive analysis from tamiz.pro examines the gap between AI agent hype and production deployment, highlighting that frameworks like LangChain, AutoGen, and Haystack with 10K+ GitHub stars signal i…

An engineer with 18 months of experience building AI agent systems across multiple teams shares hard-won lessons about shipping agents to production, highlighting the gap between benchmark performance…

Researchers formalize the execution harness of LLM agents as a learnable control layer using offline reinforcement learning, training a lightweight controller with advantage-weighted regression to imp…

AI agents that generate code and orchestrate workflows are becoming production infrastructure, but their non-deterministic outputs create measurement, compliance, and regression challenges. Benchmark …