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In this tutorial, we build a human-in-the-loop travel booking agent that treats the user as a teammate rather than a passive observer. We design the system so the agent first reasons openly by drafting a structured travel plan, then deliberately pauses before taking any action. We expose this proposed plan in a live interface where […]
As AI agents optimize how they communicate, the shift away from human-readable language underscores why transparency and interpretability are essential for building trust in autonomous systems. The post A New Frontier for AI Agents: Transparency appeared first on SAS Blogs.
Generative AI showed up in the enterprise fast. In what felt like no time, it went from something people were experimenting with to something leaders were expected to have a plan for. Not just whether to adopt it, but how it fits into the future of their organization. And underneath […] The post From AI
In this tutorial, we build a fully stateful personal tutor agent that moves beyond short-lived chat interactions and learns continuously over time. We design the system to persist user preferences, track weak learning areas, and selectively recall only relevant past context when responding. By combining durable storage, semantic retrieval, and adaptive prompting, we demonstrate how
Moonshot AI has officially brought the power of OpenClaw framework directly to the browser. The newly rebranded Kimi Claw is now native to kimi.com, providing developers and data scientists with a persistent, 24/7 AI agent environment. This update moves the project from a local setup to a cloud-native powerhouse. This means the infrastructure for complex
OpenClaw is a self-hosted personal AI assistant that runs on your own devices and communicates through the apps you already use—such as WhatsApp, Telegram, Slack, Discord, and more. It can answer questions, automate tasks, interact with your files and services, and even speak or listen on supported devices, all while keeping you in control of
Getting Started with OpenClaw and Connecting It with WhatsApp Read More »
In this tutorial, we build a self-organizing memory system for an agent that goes beyond storing raw conversation history and instead structures interactions into persistent, meaningful knowledge units. We design the system so that reasoning and memory management are clearly separated, allowing a dedicated component to extract, compress, and organize information. At the same time,
How to Build a Self-Organizing Agent Memory System for Long-Term AI Reasoning Read More »
In the world of Large Language Models (LLMs), speed is the only feature that matters once accuracy is solved. For a human, waiting 1 second for a search result is fine. For an AI agent performing 10 sequential searches to solve a complex task, a 1-second delay per search creates a 10-second lag. This latency
As AI agents gain autonomy and access to sensitive systems, emerging threats like prompt injection worms highlight how human-like security training and governance must evolve to prevent large-scale, opaque cybersecurity breaches driven by agent behavior. The post A New Frontier for AI Agents: Cybersecurity appeared first on SAS Blogs.
On Monday, a pull request executed by an AI agent to the popular Python charting library matplotlib turned into a 45-comment debate about whether AI-generated code belongs in open source projects. What made that debate all the more unusual was that the AI agent itself took part, going so far as to publish a blog
After a routine code rejection, an AI agent published a hit piece on someone by name Read More »
