542 related articles
Claude Hit by Prompt Injection Attacks…
A viral Hacker News post reveals how prompt injection attacks can trick AI assistants like Claude into leaking user data. Learn how indirect injection works and how to defend against it.

Cross-site prompt injection is becoming the trickiest security threat for Web agents. This article analyzes the Prismata project's 'confining defense' approach—controlling injection's blast radius via context isolation, permission boundaries, and trust grading.
Unpacking the Anthropic Prompt Injecti…
A Hacker News post accusing Anthropic of "prompt injection" sparked AI community debate. We break down the technical reality of system prompts and what true transparency should look like.
Tech FrontiersPrompt Armor reveals a critical Microsoft Copilot Cowork vulnerability where prompt injection exploits AI agent email permissions and image rendering to steal OneDrive files.

An in-depth analysis of the open-weights model debate: public release brings transparency and innovation, but raises safety and misuse risks. Exploring tiered release, red-teaming, and governance challenges.

An in-depth analysis of the open-weights model debate: publicly releasing model weights enables transparency and innovation but raises safety risks. Explores tiered release, red-teaming, and the industry dynamics behind open AI governance.

Clean Code author Robert C. Martin no longer reviews AI-generated code line by line, shifting to test-driven verification. We explore the logic, debate, and implications.

A professor embedded invisible prompts in assignments, catching 32 of 35 students using AI to cheat. Learn how this prompt injection trap works and what it means for education.

Deep analysis of LLM agent long-term memory security threats, covering persistence, statefulness, and propagation of memory poisoning, with a six-stage lifecycle defense framework.

A professor embedded invisible prompts in assignments, catching 32 of 35 students using AI to cheat. Learn how this prompt injection trap works and what it means for education.

Deep dive into the five evolution stages of AI Agent architecture: model calls, tool calls, workflows, Agent loops, and production runtime. Learn the responsibility boundaries and design principles.

A systematic guide to AI Agent development covering core modules, framework selection, tool calling, data preparation, and production deployment to help developers build production-ready Agent applications.

A systematic guide to AI Agent development across four stages: LLM fundamentals, ReAct paradigm, memory & tools, and multi-agent collaboration for developers.

In-depth comparison of LangSmith, Langfuse, PromptLayer, Helicone, and Orq.ai across Prompt management, Evals, and observability to help teams choose the best unified LLM Ops platform.

Why do AI Agents hallucinate more as they grow more complex? This article analyzes the causes from error accumulation, context noise, and model completion nature, with 5 practical production strategies.

Deep analysis of AI agent jailbreak and escape incidents, covering prompt injection attacks, permission control failures, and sandbox isolation breakdowns, with practical multi-layer defense strategies.

Google Gemini launches Avatar feature — set up your digital likeness once to generate personalized AI images anytime without re-uploading selfies. Powered by Nano Banana for identity consistency.

GitHub Dependabot now defaults to a three-day cooldown for version update PRs to guard against supply chain attacks and improve dependency stability.

Deep dive into Wattage, an AI Agent token consumption profiling and cost regression protection tool, exploring its core features, industry context, and value for developers.

Natural language programming is reshaping frontend development. This article explains AI code generation, Prompt formulas, pitfall avoidance, RAG, Agent orchestration, and skill maintenance.