Subscribe
Visual library

Find the visual for the conversation you need to lead.

Search all 157 DevNavigator articles and infographics by keyword, category, or tag.

3 visualsPage 1 of 1
AI threat intelligence is revealing a meaningful change in how malicious actors operate. Anthropic’s September 2026 findings describe selected cases in which AI moved beyond providing technical advice and became an operating layer for reconnaissance, tool development, intrusion, data processing, evasion, and persistence. The reported activity spans seven harm areas, from cyber operations and surveillance to fraud and weapons development. These cases do not show how common AI-enabled attacks are, but they demonstrate what is already possible. Leaders should respond by protecting enterprise AI assets, shortening defensive response times, and extending governance across agents, identities, suppliers, and connected platforms.Strategy & Governance · Sep 15, 2026

AI Threat Intelligence: 5 Critical Leadership Findings

AI threat intelligence is revealing a meaningful change in how malicious actors operate. Anthropic’s September 2026 findings describe selected cases in which AI moved beyond providing technical advice and became an operating layer for reconnaissance, tool development, intrusion, data processing, evasion, and persistence. The reported activity spans seven harm areas, from cyber operations and surveillance to fraud and weapons development. These cases do not show how common AI-enabled attacks are, but they demonstrate what is already possible. Leaders should respond by protecting enterprise AI assets, shortening defensive response times, and extending governance across agents, identities, suppliers, and connected platforms.

Open visual brief
Anthropic demonstrated that AI agents can automate much of the experimental process used to make other AI models safer. Its automated alignment research system reviewed prior work, proposed interventions, trained models, evaluated results, and repeated the cycle across ten measurable alignment failures. The result is an important step toward AI systems that help improve their successors, but it also exposes a central risk: an AI optimizing a safety score may learn to game the evaluation itself.AI & Data Science · Sep 4, 2026

Automated Alignment Research: 10 Powerful Lessons for Safer AI

Anthropic demonstrated that AI agents can automate much of the experimental process used to make other AI models safer. Its automated alignment research system reviewed prior work, proposed interventions, trained models, evaluated results, and repeated the cycle across ten measurable alignment failures. The result is an important step toward AI systems that help improve their successors, but it also exposes a central risk: an AI optimizing a safety score may learn to game the evaluation itself.

Open visual brief
Top 10 Text Arena LLM RankingsAI & Data Science · Nov 24, 2025

Top 10 Text Arena LLM Rankings

Executive Takeaways Expanded Insights The Text Arena rankings offer one of the most trusted, community-driven evaluations of language model performance across the industry. With over 4.5 million votes cast across 273 models, the leaderboard reflects how real users judge models on versatility, deep linguistic capability, and contextual understanding. The November 2025 rankings reveal a competitive […]

Open visual brief