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        <title><![CDATA[Stories by Sarah Mason on Medium]]></title>
        <description><![CDATA[Stories by Sarah Mason on Medium]]></description>
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            <title>Stories by Sarah Mason on Medium</title>
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        <item>
            <title><![CDATA[The Analytics‑Driven Approach to UX in IoT, Add‑Ons, and Companion Apps]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://www.dataology.blog/the-analytics-driven-approach-to-ux-in-iot-add-ons-and-companion-apps-e46fbd52ed05?source=rss-76f515c9c077------2"><img src="https://cdn-images-1.medium.com/max/2600/0*eRTICx6ouInaObvP" width="7383"></a></p><p class="medium-feed-snippet">Analytics defines how users understand an IoT system. It shapes the way insights appear, how device behavior is interpreted, and how&#x2026;</p><p class="medium-feed-link"><a href="https://www.dataology.blog/the-analytics-driven-approach-to-ux-in-iot-add-ons-and-companion-apps-e46fbd52ed05?source=rss-76f515c9c077------2">Continue reading on Dataology »</a></p></div>]]></description>
            <link>https://www.dataology.blog/the-analytics-driven-approach-to-ux-in-iot-add-ons-and-companion-apps-e46fbd52ed05?source=rss-76f515c9c077------2</link>
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            <category><![CDATA[best-practices]]></category>
            <category><![CDATA[ux]]></category>
            <category><![CDATA[technology]]></category>
            <category><![CDATA[iot]]></category>
            <category><![CDATA[analytics]]></category>
            <dc:creator><![CDATA[Sarah Mason]]></dc:creator>
            <pubDate>Tue, 20 Oct 2026 14:56:01 GMT</pubDate>
            <atom:updated>2026-10-20T14:56:01.477Z</atom:updated>
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        <item>
            <title><![CDATA[Bringing AI Agents to Life With Local MCP Workflows]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://www.dataology.blog/bringing-ai-agents-to-life-with-local-mcp-workflows-a9a273944b3b?source=rss-76f515c9c077------2"><img src="https://cdn-images-1.medium.com/max/2600/0*zzYelpLtYTNsyIet" width="4076"></a></p><p class="medium-feed-snippet">I&#x2019;ve been exploring how AI agents and looking to move beyond abstract demos and into real, testable workflows.</p><p class="medium-feed-link"><a href="https://www.dataology.blog/bringing-ai-agents-to-life-with-local-mcp-workflows-a9a273944b3b?source=rss-76f515c9c077------2">Continue reading on Dataology »</a></p></div>]]></description>
            <link>https://www.dataology.blog/bringing-ai-agents-to-life-with-local-mcp-workflows-a9a273944b3b?source=rss-76f515c9c077------2</link>
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            <category><![CDATA[product-development]]></category>
            <category><![CDATA[ai-agent]]></category>
            <category><![CDATA[ai]]></category>
            <category><![CDATA[technology]]></category>
            <category><![CDATA[data]]></category>
            <dc:creator><![CDATA[Sarah Mason]]></dc:creator>
            <pubDate>Thu, 15 Oct 2026 15:20:01 GMT</pubDate>
            <atom:updated>2026-10-15T15:20:01.489Z</atom:updated>
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        <item>
            <title><![CDATA[Why GitHub Still Matters]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://www.dataology.blog/why-github-still-matters-f730bb041aa5?source=rss-76f515c9c077------2"><img src="https://cdn-images-1.medium.com/max/2600/0*zEPJ-5ITFPxfySva" width="14467"></a></p><p class="medium-feed-snippet">Organizing Projects, Preserving Version History, and Building a Professional Portfolio</p><p class="medium-feed-link"><a href="https://www.dataology.blog/why-github-still-matters-f730bb041aa5?source=rss-76f515c9c077------2">Continue reading on Dataology »</a></p></div>]]></description>
            <link>https://www.dataology.blog/why-github-still-matters-f730bb041aa5?source=rss-76f515c9c077------2</link>
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            <category><![CDATA[analytics]]></category>
            <category><![CDATA[github]]></category>
            <category><![CDATA[career-development]]></category>
            <category><![CDATA[technology]]></category>
            <dc:creator><![CDATA[Sarah Mason]]></dc:creator>
            <pubDate>Tue, 06 Oct 2026 17:05:31 GMT</pubDate>
            <atom:updated>2026-10-06T17:05:31.528Z</atom:updated>
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        <item>
            <title><![CDATA[Data Evaluation: Why Lightweight Python Utilities Still Matter in Modern Analytics for Quality]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://www.dataology.blog/data-evaluation-why-lightweight-python-utilities-still-matter-in-modern-analytics-for-quality-f4445fb6b8cc?source=rss-76f515c9c077------2"><img src="https://cdn-images-1.medium.com/max/2600/0*B2-mf3nfrsVpsLer" width="5616"></a></p><p class="medium-feed-link"><a href="https://www.dataology.blog/data-evaluation-why-lightweight-python-utilities-still-matter-in-modern-analytics-for-quality-f4445fb6b8cc?source=rss-76f515c9c077------2">Continue reading on Dataology »</a></p></div>]]></description>
            <link>https://www.dataology.blog/data-evaluation-why-lightweight-python-utilities-still-matter-in-modern-analytics-for-quality-f4445fb6b8cc?source=rss-76f515c9c077------2</link>
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            <category><![CDATA[python]]></category>
            <category><![CDATA[analytics]]></category>
            <category><![CDATA[data]]></category>
            <category><![CDATA[data-quality]]></category>
            <dc:creator><![CDATA[Sarah Mason]]></dc:creator>
            <pubDate>Thu, 01 Oct 2026 14:35:59 GMT</pubDate>
            <atom:updated>2026-10-01T15:04:52.382Z</atom:updated>
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        <item>
            <title><![CDATA[Technical Editing With AI: Turning Raw Analyst Work Into Executive‑Ready Artifacts]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://www.dataology.blog/technical-editing-with-ai-turning-raw-analyst-work-into-executive-ready-artifacts-232e30e6e5bc?source=rss-76f515c9c077------2"><img src="https://cdn-images-1.medium.com/max/2600/0*CdarODLunPVUx8YT" width="5184"></a></p><p class="medium-feed-snippet">Analysts produce a tremendous amount of technical material with SQL logic, Python notebooks, data models, documentation, dashboards, and&#x2026;</p><p class="medium-feed-link"><a href="https://www.dataology.blog/technical-editing-with-ai-turning-raw-analyst-work-into-executive-ready-artifacts-232e30e6e5bc?source=rss-76f515c9c077------2">Continue reading on Dataology »</a></p></div>]]></description>
            <link>https://www.dataology.blog/technical-editing-with-ai-turning-raw-analyst-work-into-executive-ready-artifacts-232e30e6e5bc?source=rss-76f515c9c077------2</link>
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            <category><![CDATA[technology]]></category>
            <category><![CDATA[productivity]]></category>
            <category><![CDATA[agentic-workflow]]></category>
            <category><![CDATA[ai]]></category>
            <dc:creator><![CDATA[Sarah Mason]]></dc:creator>
            <pubDate>Fri, 25 Sep 2026 13:22:43 GMT</pubDate>
            <atom:updated>2026-09-25T13:22:43.756Z</atom:updated>
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        <item>
            <title><![CDATA[AI‑Enhanced Agile: Modern Tools to Strengthen Sprint Planning, Backlog Management, and Delivery for…]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://www.dataology.blog/ai-enhanced-agile-modern-tools-to-strengthen-sprint-planning-backlog-management-and-delivery-for-ba37b28d09e1?source=rss-76f515c9c077------2"><img src="https://cdn-images-1.medium.com/max/2560/0*evQ4GJwnigwMnEwP" width="2560"></a></p><p class="medium-feed-snippet">Agile has always promised adaptability, transparency, and continuous improvement. In practice, many teams struggle to maintain the&#x2026;</p><p class="medium-feed-link"><a href="https://www.dataology.blog/ai-enhanced-agile-modern-tools-to-strengthen-sprint-planning-backlog-management-and-delivery-for-ba37b28d09e1?source=rss-76f515c9c077------2">Continue reading on Dataology »</a></p></div>]]></description>
            <link>https://www.dataology.blog/ai-enhanced-agile-modern-tools-to-strengthen-sprint-planning-backlog-management-and-delivery-for-ba37b28d09e1?source=rss-76f515c9c077------2</link>
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            <category><![CDATA[ai]]></category>
            <category><![CDATA[analytics]]></category>
            <category><![CDATA[productivity-tips]]></category>
            <category><![CDATA[agile]]></category>
            <dc:creator><![CDATA[Sarah Mason]]></dc:creator>
            <pubDate>Wed, 16 Sep 2026 16:25:26 GMT</pubDate>
            <atom:updated>2026-09-16T16:25:26.038Z</atom:updated>
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        <item>
            <title><![CDATA[How Modern Analysts Turn Raw Data Into Clear, Actionable Narratives With AI‑Assisted Insight…]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://www.dataology.blog/how-modern-analysts-turn-raw-data-into-clear-actionable-narratives-with-ai-assisted-insight-20a0a5c1c908?source=rss-76f515c9c077------2"><img src="https://cdn-images-1.medium.com/max/2600/0*Puum8OWW2c5p0wMg" width="4270"></a></p><p class="medium-feed-snippet">Insight generation has always been the core of analytics work. It&#x2019;s also the part that consumes the most time. Analysts spend hours&#x2026;</p><p class="medium-feed-link"><a href="https://www.dataology.blog/how-modern-analysts-turn-raw-data-into-clear-actionable-narratives-with-ai-assisted-insight-20a0a5c1c908?source=rss-76f515c9c077------2">Continue reading on Dataology »</a></p></div>]]></description>
            <link>https://www.dataology.blog/how-modern-analysts-turn-raw-data-into-clear-actionable-narratives-with-ai-assisted-insight-20a0a5c1c908?source=rss-76f515c9c077------2</link>
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            <category><![CDATA[productivity]]></category>
            <category><![CDATA[analytics]]></category>
            <category><![CDATA[data-analysis]]></category>
            <category><![CDATA[data-storytelling]]></category>
            <category><![CDATA[generative-ai-tools]]></category>
            <dc:creator><![CDATA[Sarah Mason]]></dc:creator>
            <pubDate>Tue, 08 Sep 2026 15:13:42 GMT</pubDate>
            <atom:updated>2026-09-08T15:13:42.286Z</atom:updated>
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            <title><![CDATA[AI‑Enabled GitHub: How Copilot Transforms Documentation, Coding Habits, and Collaboration for…]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://www.dataology.blog/ai-enabled-github-how-copilot-transforms-documentation-coding-habits-and-collaboration-for-77c6ce300787?source=rss-76f515c9c077------2"><img src="https://cdn-images-1.medium.com/max/2600/0*RFXpg0FpXvOIUGY9" width="4096"></a></p><p class="medium-feed-snippet">GitHub has quietly become one of the most accessible and impactful AI&#x2011;enabled platforms for analysts, engineers, and hybrid technical&#x2026;</p><p class="medium-feed-link"><a href="https://www.dataology.blog/ai-enabled-github-how-copilot-transforms-documentation-coding-habits-and-collaboration-for-77c6ce300787?source=rss-76f515c9c077------2">Continue reading on Dataology »</a></p></div>]]></description>
            <link>https://www.dataology.blog/ai-enabled-github-how-copilot-transforms-documentation-coding-habits-and-collaboration-for-77c6ce300787?source=rss-76f515c9c077------2</link>
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            <category><![CDATA[ai]]></category>
            <category><![CDATA[generative-ai-tools]]></category>
            <category><![CDATA[analytics]]></category>
            <category><![CDATA[github-copilot]]></category>
            <dc:creator><![CDATA[Sarah Mason]]></dc:creator>
            <pubDate>Mon, 31 Aug 2026 18:36:37 GMT</pubDate>
            <atom:updated>2026-08-31T18:36:37.316Z</atom:updated>
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        <item>
            <title><![CDATA[Analyst‑Friendly AI Guardrails: How to Give Results the Context They Need]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://www.dataology.blog/analyst-friendly-ai-guardrails-how-to-give-results-the-context-they-need-931b87447e61?source=rss-76f515c9c077------2"><img src="https://cdn-images-1.medium.com/max/2000/0*OcJpl-ToAPPS2NFR" width="2000"></a></p><p class="medium-feed-snippet">AI is now woven into the analyst workflow. It drafts SQL, summarizes findings, generates documentation, and accelerates analysis. But even&#x2026;</p><p class="medium-feed-link"><a href="https://www.dataology.blog/analyst-friendly-ai-guardrails-how-to-give-results-the-context-they-need-931b87447e61?source=rss-76f515c9c077------2">Continue reading on Dataology »</a></p></div>]]></description>
            <link>https://www.dataology.blog/analyst-friendly-ai-guardrails-how-to-give-results-the-context-they-need-931b87447e61?source=rss-76f515c9c077------2</link>
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            <category><![CDATA[productivity]]></category>
            <category><![CDATA[context]]></category>
            <category><![CDATA[ai]]></category>
            <category><![CDATA[analytics]]></category>
            <dc:creator><![CDATA[Sarah Mason]]></dc:creator>
            <pubDate>Fri, 28 Aug 2026 01:16:59 GMT</pubDate>
            <atom:updated>2026-08-28T01:16:59.962Z</atom:updated>
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        <item>
            <title><![CDATA[Minimum Viable Analysis: How To Deliver Analytics Faster Without Losing Quality]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://www.dataology.blog/minimum-viable-analysis-how-to-deliver-analytics-faster-without-losing-quality-0774621d24f4?source=rss-76f515c9c077------2"><img src="https://cdn-images-1.medium.com/max/2600/0*PpfN81TYXLmIaOjh" width="4000"></a></p><p class="medium-feed-snippet">In product development, teams use the idea of a Minimum Viable Product (MVP). MVP is the smallest version of something that still delivers&#x2026;</p><p class="medium-feed-link"><a href="https://www.dataology.blog/minimum-viable-analysis-how-to-deliver-analytics-faster-without-losing-quality-0774621d24f4?source=rss-76f515c9c077------2">Continue reading on Dataology »</a></p></div>]]></description>
            <link>https://www.dataology.blog/minimum-viable-analysis-how-to-deliver-analytics-faster-without-losing-quality-0774621d24f4?source=rss-76f515c9c077------2</link>
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            <category><![CDATA[workflow]]></category>
            <category><![CDATA[analytics]]></category>
            <category><![CDATA[productivity]]></category>
            <category><![CDATA[ai-agent]]></category>
            <category><![CDATA[storytelling-for-business]]></category>
            <dc:creator><![CDATA[Sarah Mason]]></dc:creator>
            <pubDate>Tue, 18 Aug 2026 14:56:01 GMT</pubDate>
            <atom:updated>2026-08-18T14:56:01.181Z</atom:updated>
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