357 summarised stories about AI Evaluation, each linking back to the original source. Browse all topics →
Simon Willison’s Weblog 1 day ago 30
Claude Code changed its code review process from a PR gate at the end of development to continuous review while coding. Most changes are reviewed and fixed by Claude at least once before a human is asked to look. This reduces routine mistakes before human review and shifts team attention toward higher-level scrutiny.
Amazon Web Services 1 day ago 26 ● 3 sources
AWS’s SMGS Operations team built a production multi-agent system using Amazon Bedrock AgentCore and related AWS services, and they used AgentCore Evaluations to continuously test agent quality instead of relying on traditional monitoring. In a pre-production test, a configuration mismatch window cut the pass rate from 78 percent to 38 percent. The approach introduces a nine-stage, closed-loop evaluation framework with CI/CD regression gates, canary scoring, drift detection, and automated feedback loops to keep answers grounded and correct as data, prompts, tools, and models change.
TechCrunch 1 day ago 44
Elorian released its first AI model, Glimpse, as a research preview with an API and waitlist-only chat that lets the model revisit images while reasoning. Glimpse is priced at $0.60 per 1 million input tokens and $3 per 1 million output tokens. It changes the approach from one-pass image-to-text tokenization to iterative “visual scratch space” behavior (cropping, extracting video frames, and running code) aimed at stronger visual reasoning and eventually scene-to-action for robotics and other video-heavy use cases.
Fractional Futurist 1 day ago 13
The page “How to Measure the Human Cost of Agent Work” presents guidance on assessing the human impact of agent-related work, but it provides no specific methodology or results in the excerpt shown. The only concrete detail available is the credited author name, Michael Cutler. As a result, there’s not enough information here to describe measurable changes or outcomes beyond the topic being introduced.
Latent Space 1 day ago 31
Goodfire published an essay arguing that many supposed polysemanticity knots in neural networks can be resolved by further agentic analysis. It cites an earlier automated interpretability result finding only 2% of cases as legible. As a result, the piece claims interpretability is more successful and reports a global lowering of P(doom) alongside the alignment discussion.
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17 October 2026
AI governance moved from slideware to the boring-but-important mechanics of who gets to fetch, act, and prove. Meta quietly rewrote parts of its commercial terms, removing wording that appeared to let it use web content to “train” and “maintain the integrity” of its products; the update followed legal scrutiny that it could be read as broad scraping permission. At the same time, users reported that major websites are blocking AI agents from completing tasks across services—turning “agentic” demos into something closer to permissioned automation. ServiceNow is now trying to sell the glue for that reality with its AI Control Tower, positioning it as an enterprise platform to discover and govern agents across models and clouds, while a field study of 15 large-enterprise customers questioned how fully its runtime enforcement and AI lifecycle evidence hold up versus alternatives.
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