If you are a user of LLM systems that use tools (you can call them “AI agents” if you like) it is critically important that you understand the risk of …
Signal President Meredith Whittaker calls out agentic AI as having 'profound' security and privacy issues | TechCrunch
Signal President Meredith Whittaker warned Friday that agentic AI could come with a risk to user privacy. Speaking onstage at the SXSW conference in
HUGE — AI Without Giving Up Your Privacy
We're building an Agentic AI Platform running on your Device that lives with YOU, isolated from the cloud, fundamentally reimagining the relationship between humans and artificial intelligence through ownership, privacy, and massive context. In an age of capture and control, HUGE sells independence and sovereignty.
How to Deploy AI Agents for Safety
The 2025 AI Agent Index: Documenting Technical and Safety Features of Deployed Agentic AI Systems
Agentic AI systems are increasingly capable of performing professional and personal tasks with limited human involvement. However, tracking these developments is difficult because the AI agent ecosystem is complex, rapidly evolving, and inconsistently documented, posing obstacles to both researchers and policymakers. To address these challenges, this paper presents the 2025 AI Agent Index. The Index documents information regarding the origins, design, capabilities, ecosystem, and safety features of 30 state-of-the-art AI agents based on publicly available information and email correspondence with developers. In addition to documenting information about individual agents, the Index illuminates broader trends in the development of agents, their capabilities, and the level of transparency of developers. Notably, we find different transparency levels among agent developers and observe that most developers share little information about safety, evaluations, and societal impacts. The 2025 AI Agent Index is available online at https://aiagentindex.mit.edu
The 2025 AI Agent Index: Documenting Technical and Safety Features of Deployed Agentic AI Systems
Agentic AI systems are increasingly capable of performing professional and personal tasks with limited human involvement. However, tracking these developments is difficult because the AI agent ecosystem is complex, rapidly evolving, and inconsistently documented, posing obstacles to both researchers and policymakers. To address these challenges, this paper presents the 2025 AI Agent Index. The Index documents information regarding the origins, design, capabilities, ecosystem, and safety features of 30 state-of-the-art AI agents based on publicly available information and email correspondence with developers. In addition to documenting information about individual agents, the Index illuminates broader trends in the development of agents, their capabilities, and the level of transparency of developers. Notably, we find different transparency levels among agent developers and observe that most developers share little information about safety, evaluations, and societal impacts. The 2025 AI Agent Index is available online at https://aiagentindex.mit.edu
The 2025 AI Agent Index Documenting Technical and Safety Features of Deployed Agentic AI Systems
Agentic AI systems are increasingly capable of performing professional and personal tasks with limited human involvement. However, tracking these developments is difficult because the AI agent ecosystem is complex, rapidly evolving, and inconsistently documented, posing obstacles to both researchers and policymakers. To address these challenges, this paper presents the 2025 AI Agent Index. The Index documents information regarding the origins, design, capabilities, ecosystem, and safety features of 30 state-of-the-art AI agents based on publicly available information and email correspondence with developers. In addition to documenting information about individual agents, the Index illuminates broader trends in the development of agents, their capabilities, and the level of transparency of developers. Notably, we find different transparency levels among agent developers and observe that most developers share little information about safety, evaluations, and societal impacts. The 2025 AI Agent Index is available online at https://aiagentindex.mit.edu.
AI Agents: Key Concepts and How They Overcome LLM Limitations
An AI agent is an autonomous software entity that is often used to augment a large language model. Here's what developers need to know.
pguso/ai-agents-from-scratch
Demystify AI agents by building them yourself. Local LLMs, no black boxes, real understanding of function calling, memory, and ReAct patterns.
Technical Breakdown: How AI Agents Ignore 40 Years of Security Progress
AI agents pose untold risk to humanity. We must act to prevent that future | David Krueger
The pieces are falling into place for autonomous artificial intelligence. We must stop unregulated development
[Keynote 03] Simulating Emergent LLM Social Behaviors in Multi Agent Systems
Build Agent Advocates, Not Platform Agents
Language model agents are poised to mediate how people navigate and act online. If the companies that already dominate internet search, communication, and commerce -- or the firms trying to unseat them -- control these agents, the resulting platform agents will likely deepen surveillance, tighten lock-in, and further entrench incumbents. To resist that trajectory, this position paper argues that we should promote agent advocates: user-controlled agents that safeguard individual autonomy and choice. Doing so demands three coordinated moves: broad public access to both compute and capable AI models that are not platform-owned, open interoperability and safety standards, and market regulation that prevents platforms from foreclosing competition.
AI agent runs amok in Fedora and elsewhere
Agentic AI systems can be used to do a variety of things autonomously on behalf of a human user [...]
Top AI Security Incidents of 2025 Revealed | Adversa AI
Discover how AI systems are being hacked in the wild — from prompt injection to agent abuse — with real breaches, lessons, and defenses in Adversa AI’s 2025 report.
Agents Rule of Two: A Practical Approach to AI Agent Security
We've developed the Agents Rule of Two. When this framework is followed, the severity of security risks is deterministically reduced.
Privacy Considerations with AI Tools
Artificial intelligence (AI) tools come in all sorts of flavors. There are notetaking and transcription tools, chatbots, device-wide agentic AI features, grammar and writing tools, translation assistants, AI summaries, and research tools, among others. As a term, “AI” may refer to features in apps, apps themselves, third-party plug-ins, or a...