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Meet Atoms: A Vibe Coding Tool That Uses AI Agents to Build, Deploy, and Market Your App (No Code)

The concept of vibe coding is interesting; you don’t need to be a developer or software engineer to build your own applications. You can describe your idea to an AI in plain language, and it will build, edit, and refine your applications so you don’t have to write code line by line. It sounds simple […]

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Learning to lead in a hybrid human-AI enterprise

As adoption of AI agents looks set to surge by as much as 300% in the next two years, leadership teams are carefully considering the implications of a hybrid human-AI workforce.  Unlike existing enterprise-level automation that relies on manual input, AI agents are capable of autonomously coordinating complex tasks, interacting with multiple tools and environments across

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TinyFish Launches BigSet: An Open-Source Multi-Agent System That Builds Structured Live Datasets from Plain-English Descriptions

Building a structured dataset from the web is still a pipeline problem. You identify a data source, write or configure a scraper, design a schema, handle deduplication, schedule refreshes, and fix breakage when upstream sites change. That process stays roughly the same whether you do it once or a hundred times. TinyFish is releasing BigSet

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Rehumanizing global health care with agentic AI

The global health care sector is under increasing strain.  Decades of chronic underinvestment and constraints in recruitment have coincided with a surge in demand for services for aging populations. Gaps in provision are already taking a toll, with fragmented access to care and high rates of stress and burnout among staff. And it’s getting worse.

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Rethinking organizational design in the age of agentic AI

Amid rapidly growing adoption of enterprise-level AI agents, there’s a disconnect emerging between ambition and execution.  Although 85% of organizations say they want to be agentic within the next three years, 76% say their current operations and infrastructure can’t support that change. They cite a lack of readiness across people, processes, and workflows.  The sticky

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How CopilotKit Is Redefining the Agentic AI Stack in 2026

For years, AI inside software meant a chat widget bolted onto the corner of an application. You typed, the model responded with text, and you manually translated that output into whatever you actually needed it to do. It was useful the way a calculator is useful: functional, but fundamentally passive. CopilotKit, a Seattle-based startup co-founded

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Scaling creativity in the age of AI

Storytelling is core to humanity’s DNA, stemming from our impulse to express ideals, warnings, hopes, and experiences. Technology has always been woven through the medium and the distribution: from early humans’ innovation of natural pigments and charcoals for cave paintings to literal representation by the camera. The landscape of storytelling continues to shift under our

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Understanding the modern cybercrime landscape

Throughout 2025, HPE observed significant changes in how cybercriminals operate. Analyzing real-world threats, our HPE Threat Labs highlighted an industrialization of the cyber criminals’ methods in its new In the Wild Report, enabling greater scale, speed and structure in their campaigns. They typically use automation and AI to exploit longstanding vulnerabilities, and many have adopted

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Establishing AI and data sovereignty in the age of autonomous systems

When generative AI first moved from research labs into real-world business applications, enterprises made a tacit bargain: “Capability now, control later.” Feed your proprietary data into third-party AI models, and you will get powerful results. But your data passes through systems you do not own, under governance you do not set. The protections you rely

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Data readiness for agentic AI in financial services

Financial services companies have unique needs when it comes to business AI. They operate in one of the most highly regulated sectors while responding to external events that are updated by the second. As a result, the success of agentic AI in financial services depends less on the sophistication of the system and more on

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