Evals
PulseAugur coverage of Evals — every cluster mentioning Evals across labs, papers, and developer communities, ranked by signal.
- 2026-10-27 product_launch OpenAI's hosted Evals platform is being deprecated. source
5 day(s) with sentiment data
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AI evals: Measuring AI performance beyond simple output checks
AI evaluations, or "evals," are crucial for assessing AI system performance beyond simple output checks. They involve defining specific expectations, such as producing a configuration with a precise number of replicas o…
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LLM agents fail in production; tracing is key to fixing them
Production environments reveal LLM agent failures that synthetic evaluations often miss. Issues like infinite tool loops, runaway chains, and latency spikes from hidden retries are common in real-world deployments. Comp…
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OpenAI Evals service shutting down; users urged to migrate
OpenAI is discontinuing its Evals service, with read-only access ending October 31st and full inaccessibility by November 30th. The Agent Builder and v1/prompts API will also be discontinued on the latter date. Users ar…
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OpenAI to deprecate hosted Evals platform by November 2026
OpenAI is deprecating its hosted Evals platform, with existing evaluations becoming read-only on October 31, 2026, and the dashboard and API shutting down entirely on November 30, 2026. Users are advised to export their…
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AI Agent Learns Terminology with Custom BLEU Score
The author details the creation of a small AI agent designed to learn and utilize specific terminology. This agent was developed using tools like LangChain and Python, and it was trained to evaluate its own performance …
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LLM production issues highlighted by new three-layer evaluation setup
A three-layer evaluation setup is proposed to bridge the gap between LLM performance in testing environments and their real-world application. This approach emphasizes that offline benchmark scores are merely hypotheses…
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OpenAI offers multiple agent development options with varying control levels
OpenAI offers several options for developers building agentic applications, each with different levels of control over the agent loop. The Responses API requires developers to manage the loop entirely, handling tool exe…
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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…