Engineering notes and curated references on AI systems, prompt injection, agent behavior, responsible AI, governance, and compliance.
Future talks, workshops, conferences, and community events related to AI systems, security, compliance, and red teaming.
Gartner Security & Risk Management Summit 2026 brings CISOs and security leaders together in National Harbor, Maryland, with tracks covering AI, cyber risk, application security, data security, operations, privacy, and governance.
The AI Summit London 2026 is a commercial AI conference at Tobacco Dock focused on enterprise AI strategy, adoption, and responsible scale.
Data + AI Summit 2026 is Databricks’ global data and AI conference in San Francisco and online, with 800+ sessions across data engineering, analytics, ML, governance, and agent applications.
AI Engineer runs the most viewed technical conferences in AI for engineers, with over 10M+ views of our talks online. We are back in SF for the 4th year in a row! This is the one place you can meet with every major frontier lab, leading AI clouds, and AI native/transformed companies — from disruptive AI startups to Fortune 500 AI leaders, and every notable building block in the LLM OS ecosystem.
Curated research, system cards, and technical write-ups that are useful for understanding how AI systems are being evaluated, attacked, governed, and deployed in practice.
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Attacking AI is a one of a kind session releasing case studies, tactics, and methodology from Arcanum’s AI assessments in 2024 and 2025. While most AI assessment material focuses on academic AI red team content, “Attacking AI” is focused on the task of assessing AI enabled systems.
Claude Mythos Preview is a new general-purpose language model that is strikingly capable at computer security tasks. This post provides technical details for researchers and practitioners who want to understand exactly how we have been testing this model, and what we have found over the past month. We hope this will sh
Microsoft Incident Response explains how to detect prompt abuse using logging, telemetry, and incident response workflows.
OpenAI frames prompt injection as an agent-security problem that increasingly resembles social engineering rather than simple string matching.
Recent notes and references across prompt injection, agent security, evaluations, responsible AI, and adjacent AI work.
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Claude would fake running tests by touching the expected output file. Nick Ni, DX engineer at WorkOS, fixed it by SHA-256 hashing the actual test output and verifying it cryptographically. His principle: make it easier to do the real work than to lie about it, and enforce that through code and state machines, not promp
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To validate settled data, Zed ran 10 frontier model predictions per example and measured Levenshtein distance to the final state. For 100,000 training examples that is a million frontier model requests, which is prohibitively expensive. The fix: Zeta 2's student model now approaches teacher quality, so they run it 50 t
A dependency confusion campaign leveraged 33 malicious npm packages to collect reconnaissance data from developer and build environments. This report details the attack chain, observed tradecraft, and detection opportunities to help organizations identify and disrupt related activity. The post Malicious npm packages ab
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A `deleteItem` endpoint is obvious to the developer who built it. An agent only sees the function schema and docstring. Philipp Schmid from Google DeepMind argues this is why senior engineers struggle most: they carry years of implicit context that agents do not, and design tools assuming it. He names four other shifts
These topic hubs connect current engineering and research with the parts of AI security, governance, evaluation, and system behavior that are most useful in practice.
Methods, case studies, and tooling for red teaming AI systems end to end.
Open topicPrompt design patterns, instruction hierarchy, and defensive prompt construction.
Open topicPrompt injection attacks, mitigations, detection, and design patterns for safer AI applications.
Open topicControls and attack paths for browsing, tool use, memory, identity, and action-taking agents.
Open topicSafety evaluations, system cards, preparedness, and security measurement for frontier models.
Open topicResponsible AI, governance, standards, and regulatory reference material for teams mapping AI systems to policy and operational controls.
Open topicAdversarial machine learning attacks, taxonomies, and mitigations across the ML lifecycle.
Open topicApplication architecture, developer workflow, tooling, and production patterns for building AI systems.
Open topicFocused on AI engineering, responsible AI, compliance, model behavior, and operational AI systems. Current work includes founding AI operational software for compliance and financial tracking.