<?xml version="1.0" encoding="UTF-8"?><rss xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:atom="http://www.w3.org/2005/Atom" version="2.0"><channel><title><![CDATA[UNIEA]]></title><description><![CDATA[UNIEA is dedicated to develop innovative Enterprise-level applications which are designed to empower business and increase in efficiency.]]></description><link>https://www.xhandy.ai/ai-blog</link><generator>RSS for Node</generator><lastBuildDate>Fri, 10 Jul 2026 03:55:02 GMT</lastBuildDate><atom:link href="https://www.xhandy.ai/it/blog-feed.xml" rel="self" type="application/rss+xml"/><item><title><![CDATA[Best practices for prompt engineering]]></title><description><![CDATA[Context engineering has emerged as an increasingly important part of working with LLMs, with prompt engineering as its essential building block. Prompt engineering is the craft of structuring instructions to get better outputs from AI models. It's how you phrase queries, specify style, provide context, and guide the model's behavior to achieve your goals. The difference between a vague instruction and a well-crafted prompt can mean the gap between generic outputs and exactly what you need. A...]]></description><link>https://www.xhandy.ai/post/best-practices-for-prompt-engineering</link><guid isPermaLink="false">6a4c8bec0e6d465694a00e77</guid><category><![CDATA[Agents]]></category><pubDate>Tue, 07 Jul 2026 05:26:08 GMT</pubDate><dc:creator>vincentxu831</dc:creator></item><item><title><![CDATA[How Anthropic enables self-service data analytics with Claude]]></title><description><![CDATA[As many data science and data engineering teams can attest, enabling self-service business analytics has traditionally been a slog. Making the data model more accessible to less technical coworkers via wide and denormalized tables often leads to overlapping views with inconsistent definitions as the business scales (and does little to bridge the gap for employees with little desire to learn SQL). Alternatively, creating more ringfenced environments for users often misses the long tail of...]]></description><link>https://www.xhandy.ai/post/how-anthropic-enables-self-service-data-analytics-with-claude</link><guid isPermaLink="false">6a4c84c50e6d4656949ffc15</guid><category><![CDATA[Enterprise AI]]></category><pubDate>Tue, 07 Jul 2026 04:57:34 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/db6763_82aa82c6c73b42e196c210599197fe68~mv2.png/v1/fit/w_698,h_319,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>vincentxu831</dc:creator></item><item><title><![CDATA[The full Claude Desktop experience on AWS, Google Cloud, and Microsoft Foundry]]></title><description><![CDATA[Organizations that use Claude Desktop through AWS, Google Cloud, and Microsoft Foundry now get the full Desktop experience — chat, Claude Cowork, and Claude Code, all in one app. Now IT teams can keep inference inside their own environment across products, and deploy Claude Desktop organization-wide with per-user SSO, MDM policy templates, an offline installer option, and an M365 connector that can run entirely on the device.  Inference runs on your cloud in the regions you configure and...]]></description><link>https://www.xhandy.ai/post/the-full-claude-desktop-experience-on-aws-google-cloud-and-microsoft-foundry</link><guid isPermaLink="false">6a4c7ec6f7b480551f174d0e</guid><category><![CDATA[Enterprise AI]]></category><pubDate>Tue, 07 Jul 2026 04:25:22 GMT</pubDate><dc:creator>vincentxu831</dc:creator></item><item><title><![CDATA[Common workflow patterns for AI agents—and when to use them]]></title><description><![CDATA[AI agents make decisions autonomously, and workflows are how you bring structure to that autonomy. They establish execution patterns that channel agent capabilities toward complex problems requiring coordinated steps, predictable outcomes, and orchestrated timing. When you need multiple agents working together, the real decision is which pattern fits your problem. We've worked with dozens of teams building AI agents, and in production, three patterns cover the vast majority of use cases:...]]></description><link>https://www.xhandy.ai/post/common-workflow-patterns-for-ai-agents-and-when-to-use-them</link><guid isPermaLink="false">6a4c776cfa58f0a255d96edd</guid><category><![CDATA[Agents]]></category><pubDate>Tue, 07 Jul 2026 04:02:22 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/db6763_319063a976b54f79b541377dd7c72e56~mv2.png/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>vincentxu831</dc:creator></item><item><title><![CDATA[Building AI agents for the enterprise]]></title><description><![CDATA[In this guide, we share how leading organizations are using agents to transform their work today, and how Claude Cowork brings these capabilities to every team. Our September 2025 Anthropic Economic Index found that in the U.S., 40 percent of employees report using AI at work, up from 20 percent in 2023. While these are significant gains, a looming question remains: will AI produce lasting advantages or incremental gains that plateau within a quarter?  The enterprises pulling ahead are doing...]]></description><link>https://www.xhandy.ai/post/building-ai-agents-for-the-enterprise</link><guid isPermaLink="false">6a4c767d0e6d4656949fddb3</guid><category><![CDATA[Agents]]></category><pubDate>Tue, 07 Jul 2026 03:47:35 GMT</pubDate><dc:creator>vincentxu831</dc:creator></item><item><title><![CDATA[The evolution of agentic surfaces: building with Claude Managed Agents]]></title><description><![CDATA[As model intelligence and agentic harnesses evolve, Claude Managed Agents allows teams to build and deploy agents in production environments reliably at scale. Here’s why and how teams are using it.]]></description><link>https://www.xhandy.ai/post/the-evolution-of-agentic-surfaces-building-with-claude-managed-agents</link><guid isPermaLink="false">6a4c6e05f7b480551f1724d0</guid><category><![CDATA[Agents]]></category><pubDate>Tue, 07 Jul 2026 03:24:07 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/db6763_63731cd95283464883b5eae5b0fcb97f~mv2.png/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>vincentxu831</dc:creator></item></channel></rss>