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Category: LLMOps

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  • Jamie Gillenwater

    February 19, 2026
    LLMOps

    Prompt Learning: Using Natural Language to Optimize LLM Systems

    Your customers expect better and more consistent results than your AI agent can deliver. You manually tweak a prompt, test…

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    Prompt Learning: Using Natural Language to Optimize LLM Systems
  • Sharon Campbell-Crow

    February 18, 2026
    LLMOps

    LLM-as-a-Judge: How to Build Reliable, Scalable Evaluation for LLM Apps and Agents

    LLM-as-a-judge is an evaluation method for assessing the output quality of AI apps. Think of it as a mechanism that…

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    LLM-as-a-Judge: How to Build Reliable, Scalable Evaluation for LLM Apps and Agents
  • Collin Cunningham

    February 17, 2026
    LLMOps, Product

    Optimizing AI IDEs at Scale

    Using AI development tools at scale comes with real overhead for every engineer. It’s an additional cost layered on top…

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    Optimizing AI IDEs at Scale
  • Team Comet

    February 17, 2026
    Industry, LLMOps, Product

    Comet Recognized in 2026 Gartner® Market Guide for AI Evaluation and Observability Platforms

    We are excited to announce that Comet has been included as a Representative Vendor in the Gartner Market Guide for…

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    Comet Recognized in 2026 Gartner® Market Guide for AI Evaluation and Observability Platforms
  • Sharon Campbell-Crow

    February 5, 2026
    LLMOps

    Model Context Protocol: How AI Agents Connect to Your Data

    The Model Context Protocol (MCP) emerged in late 2024 as the architectural solution for AI agent connectivity. In 2023, LLMs…

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    Model Context Protocol: How AI Agents Connect to Your Data
  • Sharon Campbell-Crow

    January 28, 2026
    LLMOps

    What is LLM Observability? The Ultimate Guide for AI Developers

    If your LLM application or agent sends your user a hallucinated answer, do you know when and why it happened?…

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    What is LLM Observability? The Ultimate Guide for AI Developers
  • Kelsey Kinzer

    January 27, 2026
    LLMOps

    Meta Prompting: Use LLMs to Optimize Prompts for AI Apps & Agents

    Meta prompting is a type of prompt engineering that zooms out from the specific content of a single prompt to…

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    Meta Prompting: Use LLMs to Optimize Prompts for AI Apps & Agents
  • Jamie Gillenwater

    January 22, 2026
    LLMOps

    Chain-of-Thought Prompting: A Guide for LLM Applications and Agents

    When Google researchers asked GPT-3 to solve grade-school math problems, the model answered 17.9 percent of the problems correctly. When…

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    Chain-of-Thought Prompting: A Guide for LLM Applications and Agents
  • Jamie Gillenwater

    January 15, 2026
    LLMOps

    Prompt Tuning: Parameter-Efficient Optimization for Agentic AI Systems

    You’ve built an agentic system that coordinates retrieval, reasoning, and response generation across multiple specialized tasks. Now you need to…

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    Prompt Tuning: Parameter-Efficient Optimization for Agentic AI Systems
  • Jamie Gillenwater

    January 12, 2026
    LLMOps

    MIPRO: The Optimizer That Brought Science to Prompt Engineering

    You know the routine: Write your first prompt, and then spend hours manually tweaking prompts, testing variations, and documenting what…

    Read

    MIPRO: The Optimizer That Brought Science to Prompt Engineering
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