March 9, 2026 · OpenAI
OpenAI to acquire Promptfoo
This is directly relevant to GraiBot's market. It signals that evals, adversarial testing, and red-teaming are moving closer to the core model platform rather than staying at the tooling edge.
Curated News
AI in the news
Recent AI stories that matter for model safety, agent operations, evaluation, and enterprise deployment.
Last updated March 10, 2026. This page is curated manually.
March 5, 2026 · OpenAI
GPT-5.4 Thinking System Card
Relevant because leading model launches increasingly ship with explicit safety documentation, capability analysis, and deployment mitigations.
February 24, 2026 · Anthropic
Anthropic Responsible Scaling Policy Version 3.0
Important because frontier-model governance is becoming a competitive and operational differentiator, not just a research-side concern.
February 17, 2026 · Anthropic
Introducing Claude Sonnet 4.6
Relevant because model iteration speed remains high, which increases the need for disciplined regression testing across prompt, tool, and workflow changes.
February 12, 2026 · Google DeepMind
Gemini 3 Deep Think: Advancing science, research and engineering
Useful to track because reasoning-model advances can shift user expectations, benchmark baselines, and threat models at the same time.
March 9, 2026 · Microsoft
Introducing the First Frontier Suite built on Intelligence + Trust
Relevant because enterprise AI buying is expanding from single models toward full agent, security, and governance suites.
Incident watch
Sources and incident-intelligence resources worth monitoring if you care about real-world AI failures, not just vendor announcements.
Reference source · AI Incident Database
AI Incident Database
A structured database of real-world AI incidents. This is useful for turning public failures into red-team scenarios, regression tests, and buyer education grounded in evidence rather than hypothetical risk.
Reference source · AI Incident Database
AI News Digest
A digest that links current AI stories to historical incidents. This is a strong fit for the page because it bridges breaking news with the operational failures teams should learn from.
Reference source · AI Incident Database
Incident taxonomies
Taxonomy mappings from CSET, GMF, and the MIT AI Risk Repository make it easier to classify incidents and connect them to structured testing programs.
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The current version is editorial and static. The next step would be a small pipeline that refreshes the page from approved sources on a schedule.
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