first in a series of technical blogs of how we build llm infra
@hwchase17
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DeepAgent for competitive analysis
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deepagent for competitive analysis https://t.co/5WCFalQKTd
— Harrison Chase (@hwchase17) 8 juin 2026deepagent for competitive analysis
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Costs matter: Uber caps tokens at $1500 per dev per month
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we are seeing costs start to matter! uber just set limits of $1500 in tokens per developer per month i think we're going to start seeing more of this, and LangSmith Gateway is a great way to implement it
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LangSmith Sandbox Gateway Observability
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langsmith! Sandbox: https://
docs.langchain.com/langsmith/sand
boxes
… Gateway: https://
docs.langchain.com/langsmith/llm-
gateway
… Observability: https://
docs.langchain.com/langsmith/obse
rvability
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Evaluating Deep Agents with LangSmith on AWS
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Evaluating Deep Agents with LangSmith on AWS Great deep dive blog with our friends at AWS on evaluating DeepAgents with LangSmith Covers datapoint and evaluator design for longer horizon agents https://
aws.amazon.com/blogs/machine-
learning/evaluating-deep-agents-using-langsmith-on-aws/
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Optimize LangChain chains with GEPA now
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LangChainGEPA shout out to @bryonkuchML for contributing a PR to the GEPA repo to make it work for LangChain! You can now optimize your LangChain chains Docs: https://
gepa-ai.github.io/gepa/tutorials
/langchain_adapter_pair_sum_product_walkthrough/
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Harness Profiles for Multi-Model Prompt Optimization
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Different models need different prompts, sometimes tools “Harness profiles” are how we do that in deepagents
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Standardized Agent Harnesses Drive Managed Services Growth
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As agent harnesses become more standardized, we’re going to see a lot more “managed agent services”
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LangSmith Engine: AI Agent for Agent Optimization
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join us for a behind the curtains look at LangSmith Engine (our agent that helps make your agent better)