Evals
PulseAugur coverage of Evals — every cluster mentioning Evals across labs, papers, and developer communities, ranked by signal.
8 day(s) with sentiment data
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AI Engineer Job Market Demands Advanced Skills Beyond Basic Roadmaps
The job market for AI engineers is rapidly expanding, with AI-skilled roles growing significantly faster than the general job market and commanding higher salaries. However, a common roadmap focusing on buzzwords like R…
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Skybridge v2 ships new MCP protocol with Evals testing framework
Skybridge has released version 2, introducing a new MCP protocol that has undergone significant changes, including becoming stateless and removing session IDs. This update necessitated a rebuild of the server architectu…
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Claude Code introduces skill management tools to boost AI efficiency
Teams are adopting new strategies to manage AI skills, focusing on efficiency and cost-effectiveness. A key development is the introduction of '/skill-doctor' by Claude Code, which identifies unused or costly skills, en…
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AI agent evals need fresh data and multi-layer testing
Ensuring the reliability of AI agents in production requires robust evaluation methods beyond simple scoring. The author highlights the critical importance of dataset freshness, warning that static datasets can lead to …
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LLM evaluations integrated into .NET CI/CD pipelines as release gates
Integrating evaluation harnesses into .NET CI/CD pipelines can serve as release gates for LLM changes, helping to automatically detect regressions, safety violations, and cost spikes before deployment. A real-world exam…
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LLM learning roadmap: Build bots, knowledge assistants, and advisors
This guide outlines a practical roadmap for learning Generative AI and LLM engineering through hands-on projects. It suggests starting with building a Lead Triaging Bot to understand LLM APIs and prompt engineering, fol…
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Figma hires AI Models design lead, recruits for design inference roles
Figma has hired Elou, who will lead design for the AI Models team. The team is actively recruiting for roles focused on evals, judge, and rubric development to enable AI models to infer design elements. This hiring init…
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Top 5 LLM Evaluation Frameworks for Release Engineering Ranked
A recent analysis highlights Promptfoo as the leading LLM evaluation framework for release engineering, particularly for its CI/CD integration that can block builds on failed tests. DeepEval is recommended for Python-ba…
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AI vendors Anthropic, OpenAI risk user data loss with unannounced tool shutdowns
Two major AI vendors, Anthropic and OpenAI, are sunsetting critical prompt management and evaluation tools, but lack of clear deprecation warnings poses a significant risk to users. Anthropic's updated Workbench will no…
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AI testers resist traditional labels, adopt 'validation engineering'
AI professionals are reportedly avoiding traditional testing terminology, opting for terms like "evals" or "validation engineering" instead of "testers" or "QA/QE." This shift in language suggests a desire to differenti…
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Supabase releases open-source benchmark for AI coding agents · 2 sources tracked
Supabase has released an open-source benchmark and framework called Evals to evaluate AI coding agents. The tool tests agents like Claude Code, Codex, and OpenCode on real-world Supabase tasks, such as schema creation a…
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LLM judges introduce systematic biases, skewing evaluations
Using Large Language Models (LLMs) as judges for evaluating other LLM outputs introduces systematic biases, such as position, verbosity, and self-preference, which cannot be averaged out like random noise. These biases …
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New AI tools aim to improve agent reliability and developer control
Agnost AI has launched a tool designed to identify and fix AI agent failures that occur in real-world production environments, which are often missed by traditional testing methods like Evals. The platform analyzes live…
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AI Engineering Trends: Harnessing and Evaluating Advanced Systems
The field of AI engineering is seeing significant trends in harness engineering and evaluation methods. These advancements are crucial for developing and refining artificial intelligence systems. The discussion highligh…
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LLMOps integrates Evals, Observability, and Security into CI/CD pipelines
This article details the implementation of LLMOps, a specialized form of MLOps focused on managing Large Language Models. It emphasizes the integration of Evals, Observability, and Security into automated CI/CD pipeline…
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AI Agents Enhanced Via Evals: Measure, Analyze, Improve Cycle
This article discusses how to improve AI agent quality through a continuous cycle of measurement, analysis, improvement, and re-measurement using the Evals framework. It emphasizes the importance of quantitatively asses…