Claude Opus 4.7 is on Replicate. Anthropic's most capable model. Step-change in agentic coding. 3x better vision. 1M context. Try it now:
AI
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Evaluator Templates for Production Agent Deployment
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We built evaluator templates around the most common eval requirements when putting agents into production. 30+ customizable templates are now available, including: LLM-as-judge evaluators with tuned prompts Rule-based code evaluators Also available in openevals v0.2.0,
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LangSmith Evaluators Hub: Centralized Management for AI Workspace
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The Evaluators tab in LangSmith is a simple way to manage centrally. Our new hub surfaces all evaluators in your workspace, regardless of project. Build evaluators once, apply everywhere.
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LangSmith Evaluation: New Reusable Evaluator Templates
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New in LangSmith Evaluation:
— LangChain (@LangChain) 16 avril 2026
✅ Evaluator template library
✅ Reusable evaluators
Everything you need to know → https://t.co/OcHAwAdwAu pic.twitter.com/tE6RktsXxiNew in LangSmith Evaluation: Evaluator template library Reusable evaluators Everything you need to know → https://
langchain.com/blog/reusable-
langsmith-evaluator-templates?utm_source=x&utm_medium=social
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Opus 4.7 Intelligence Improvements and Effective Usage Tips
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Opus 4.7 feels more intelligent, agentic, and precise than 4.6. It took a few days for me to learn how to work with it effectively, to fully take advantage of its new capabilities. Will post a few more tips throughout the day, starting with this blog post:
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Phasing Out MRCR: Rethinking Long Context Evaluation Methods
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We kept MRCR in the system card for scientific honesty, but we've actually been phasing it out slowly. Two reasons: (1) it's built around stacking distractors to trick the model, which isn't how people actually use long context, and (2) we care more about applied
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MRCR Phased Out: Focus Shifts to Applied Long-Context
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We kept MRCR in the system card for scientific honesty, but we've actually been phasing it out slowly. Two reasons: (1) it's built around stacking distractors to trick the model, which isn't how people actually use long context, and (2) we care more about applied long-context
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Jobs AI Won’t Touch: Future of Work Analysis
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The Jobs #AI Won't Touch
by @vriparbelli @Forbes Learn more: https://
buff.ly/VSuZI3j #ArtificialIntelligence #MachineLearning #ML #DL -
AI Export Restrictions Harm Innovation and US Leadership
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Completely agree with Jensen!
— clem 🤗 (@ClementDelangue) 16 avril 2026
Not exporting AI out of fear is classic case where the cure would be 100x worse than the disease. You slow down innovation, progress and US technology and economic leadership in the foolish hope that you'll prevent an edge case that hasn't even… https://t.co/ngAW6NMkLwCompletely agree with Jensen! Not exporting AI out of fear is classic case where the cure would be 100x worse than the disease. You slow down innovation, progress and US technology and economic leadership in the foolish hope that you'll prevent an edge case that hasn't even
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LangSmith Launches Startup Program with AI Agent Tools
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LangSmith for Startups gives early stage teams the tooling and community they need to iterate faster and win bigger.
— LangChain (@LangChain) 16 avril 2026
Observe, evaluate, and deploy your agents — now with free credits to help you get started.
Our Scale program offers:
– $10,000 in LangSmith credits
– Exclusive… pic.twitter.com/6r2u8OIL4cLangSmith for Startups gives early stage teams the tooling and community they need to iterate faster and win bigger. Observe, evaluate, and deploy your agents — now with free credits to help you get started. Our Scale program offers:
– $10,000 in LangSmith credits
– Exclusive