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ANKUSH CHOUDHARY JOHALApr 29, 2026 • 12 min read
Benchmark: Ragas 0.1 vs. LangSmith 2.0: RAG Evaluation Speed for 1k Queries
Processing 1,000 RAG evaluation queries takes Ragas 0.1 47 seconds and LangSmith 2.0 192 seconds on....
#benchmark#ragas#langsmith#evaluation
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ANKUSH CHOUDHARY JOHALApr 28, 2026 • 16 min read
LangChain 0.2.10 vs. LangSmith 0.12: LLM Chain Debugging Efficiency
\n In 2024, 68% of LLM-powered applications spend more engineering hours debugging chains than...
#langchain#0210#langsmith#chain
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Jordan Bourbonnais5d ago • 3 min read
The Silent Killer of AI Agent Deployments: Why Your LLM Monitoring Stack is Already Broken
You deployed that shiny new AI agent to production Monday morning. By Wednesday, you're getting Slac...
#langsmith#alternatives#langchain
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ANKUSH CHOUDHARY JOHALApr 29, 2026 • 16 min read
Deep Dive: LangSmith 0.3’s New LLM Monitoring Pipeline – How It Cuts Debug Time by 40%
After benchmarking 12 production LLM applications across 3 enterprise teams, LangSmith 0.3’s new...
#deep#dive#langsmith#monitoring
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ANKUSH CHOUDHARY JOHALApr 29, 2026 • 15 min read
How to Implement 2026 AI Governance with LangSmith 0.5 and WhyLabs 1.0
By 2026, 78% of enterprises will face regulatory fines for ungoverned AI deployments, per Gartner’s....
#implement#2026#governance#langsmith
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ANKUSH CHOUDHARY JOHALApr 30, 2026 • 14 min read
LangSmith vs. Weights & Biases: LLM Pipeline Observability Overhead for RAG Applications
In 2024, 72% of RAG pipelines in production suffer from undiagnosed observability overhead, adding.....
#langsmith#weights#biases#pipeline
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ANKUSH CHOUDHARY JOHALApr 28, 2026 • 19 min read
Deep Dive: How OpenTelemetry 1.20 and LangSmith 2026 Power AI Observability for LLM-Powered APIs
In 2025, 72% of LLM-powered API outages were traced to unobservable prompt chains, with mean time to...
#deep#dive#opentelemetry#langsmith
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