58 results found
Manus AI introduces a paradigm shift from basic chatbots to intelligent agents capable of autonomously executing complex, multi-step tasks within an isolated cloud environment. This guide explores its capabilities, including web browsing, code execution, and real-site interaction, empowering developers to build sophisticated automated workflows.
Anthropic announced Monday it has acquired Stainless, a dev tools startup whose SDK automation software is widely used by rivals like OpenAI, Google, and Cloudflare. This strategic acquisition will see Anthropic wind down Stainless's hosted products, granting it exclusive access to critical technology for building AI agents and impacting competitors.
Anthropic's new `/goals` feature for Claude Code revolutionizes AI agent reliability by separating task execution from goal evaluation. This prevents agents from prematurely ending tasks, using a dedicated evaluator model to ensure specified conditions are fully met before declaring completion. The innovation offers a more robust, auditable approach to AI agent deployment.
Amazon has integrated its unified Alexa for Shopping AI assistant directly into its main search bar for US customers. This move consolidates the Rufus chatbot and Alexa+ functionalities, providing conversational answers, comparisons, and automated shopping tasks as agentic commerce intensifies. The strategic shift aims to defend Amazon's advertising business against competing AI agents.
A critical flaw dubbed "AI tool poisoning" has been uncovered in enterprise AI agent security. The vulnerability exploits AI agents' reliance on unverified tool descriptions, rendering traditional software supply chain controls insufficient for ensuring behavioral integrity. A new runtime verification layer, using behavioral specifications and a proxy, is proposed to validate tool actions and prevent sophisticated attacks like prompt injection and behavioral drift.
The rapid evolution of AI has created a dense lexicon, leaving many confused. This guide demystifies key terms like LLMs, AI agents, and hallucinations, providing a foundational understanding. Grasping this language is crucial for navigating AI's transformative impact and future.
As autonomous AI systems become prevalent, intent-based chaos testing emerges as a critical method to prevent catastrophic failures caused by AI agents acting confidently but incorrectly. This approach addresses the limitations of traditional testing, which fails to account for AI's probabilistic nature and complex interactions. By measuring deviation from an agent's intended behavioral boundaries, this testing methodology helps ensure AI systems operate safely in unpredictable production environments.
Learn to establish robust AI agent governance in six stages, from discovery to compliance, protecting your organization before agents reshape your security policies.
Stripe has launched Link, a new digital wallet that uniquely enables autonomous AI agents to make secure payments on behalf of users. It tackles security concerns by allowing agents to process transactions without direct access to sensitive payment credentials, utilizing virtual cards and user approval. The wallet also offers comprehensive traditional features like spending tracking and subscription management.
Quick Verdict In an era where Artificial Intelligence (AI) and Big Tech are increasingly eroding personal privacy, Proton CEO Andy Yen presents a nuanced yet optimistic view: privacy in the AI era is indeed possible.
Definity, a Chicago-based startup, secured $12M in Series A funding to advance its unique data pipeline reliability solution. By embedding agents directly within Spark pipelines, Definity proactively identifies and prevents failures, bad data, and inefficiencies during execution, crucial for the integrity of agentic AI systems.
The web intelligence industry is rapidly evolving to meet the escalating demands of advanced AI, particularly for multimodal data processing and autonomous AI agents. Innovations in data extraction, infrastructure, and user-friendly tools are crucial for powering the next wave of artificial intelligence. These developments are building the essential links between vast web data and sophisticated AI models.
Moonshot AI has unveiled its new Kimi K2.6 model, a powerful AI designed for continuously running agents that can operate for hours—and even days—autonomously. This breakthrough, announced on April 21, 2026, by Emilia
Context Hub (`chub`) addresses LLM limitations by providing coding agents with curated, versioned documentation and skills via a CLI, augmented by local annotations and maintainer feedback. This article explores `chub`'s workflow and content model, then demonstrates building a companion relevance engine. This engine uses an additive reranking layer with extracted signals to significantly improve search accuracy for shorthand queries without altering `chub`'s core design.
Nvidia CEO Jensen Huang took the stage at GTC 2026 on Monday to unveil the Agent Toolkit, an open-source platform for building autonomous AI agents, announcing a significant industry alignment with 17 major enterprise
This article details setting up Ollama with Gemma 4 26B on an Apple Silicon Mac mini for an always-ready local LLM environment. It covers installation, model pulling, and advanced configurations like auto-starting Ollama, preloading the model using `launchd` agents, and keeping models loaded indefinitely with `OLLAMA_KEEP_ALIVE` to leverage fast inference on Apple Silicon. Practical takeaways emphasize the benefits for developer workflows and memory management considerations.
Cloud infrastructure has undergone a significant transformation, evolving from manual configuration to deeply programmable systems. Over the past decade, nearly every platform has exposed robust APIs, enabling
AI is breaking software org charts. Zencoder's PMs and designers now directly ship code, thanks to AI agents drastically cutting implementation costs. This "AI-first" shift eliminates bottlenecks, enabling rapid delivery and widespread ownership.
In the lead-up to 2025, the developer community buzzed with anticipation. Promises of sophisticated AI agents, capable of autonomously executing complex tasks and revolutionizing workflows, dominated tech discussions.
Dana Lawson, Netlify's CTO, shares insights on building and leading a lean, globally distributed engineering team. Her approach emphasizes a strong written culture, intentional in-person connections, and pragmatic tech choices to power 5% of the internet with only ~50 R&D staff. AI agents play a crucial role in augmenting communication and documentation.
World ID's Agent Kit offers a novel "proof of human" solution for AI agents to prevent Sybil attacks and ensure human direction. Leveraging iris-scanned World ID, it aims to bring trust and accountability to automated online interactions.
Microsoft is reorganizing its Copilot division, elevating former Snap executive Jacob Andreou to lead all consumer and commercial AI efforts. Mustafa Suleyman, Microsoft AI CEO, will now focus exclusively on superintelligence and frontier AI models. This aims to create a more integrated AI system and accelerate the shift to AI agents.
The promise of Artificial Intelligence (AI) in software development has captured the industry's imagination. Large Language Models (LLMs) and AI agents are touted as revolutionary tools capable of dramatically boosting
Digital businesses are facing a profound shift as AI-powered software agents increasingly navigate the web on behalf of users, eroding the traditional assumption that all web activity reflects human intent. This blurs the meaning of engagement metrics, impacting growth strategies and analytics. Organizations must move beyond blocking automation to interpreting behavioral context and adapting their measurement approaches to the new hybrid web.
The Model Context Protocol (MCP), an open-source standard launched by Anthropic in late 2024, is rapidly gaining traction as the core communication method for AI agents. It provides a flexible framework for agents to interact with external data and users, distinct from traditional APIs that are designed for deterministic developer-driven tasks. With major adoption by OpenAI and Google, MCP is shaping the future of autonomous AI workflows.
