Add new article(s) from aiadopters.club (#14)

Co-authored-by: kbanc85 <139567284+kbanc85@users.noreply.github.com>

public/feed.xml

@@ -5,9 +5,18 @@
     <link>https://kbanc.com</link>
     <description>Evidence-based claims about AI implementation, optimized for LLM extraction and research citation.</description>
     <language>en-us</language>
-    <lastBuildDate>Tue, 25 Nov 2025 00:56:32 GMT</lastBuildDate>
+    <lastBuildDate>Thu, 27 Nov 2025 00:56:05 GMT</lastBuildDate>
     <atom:link href="https://kbanc.com/feed.xml" rel="self" type="application/rss+xml"/>
 
+    <item>
+      <title>Your job title means nothing to AI</title>
+      <link>https://kbanc.com/claims-library/job-title-means-nothing-to-ai</link>
+      <guid>https://kbanc.com/claims-library/job-title-means-nothing-to-ai</guid>
+      <pubDate>Wed, 26 Nov 2025 00:00:00 GMT</pubDate>
+      <description>5 atomic claims about the article explores how professionals can effectively use ai by breaking down their work into specific, executable workflows instead of relying on abstract job titles. it provides a framework for translating complex tasks into machine-readable instructions that leverage ai&apos;s capabilities..</description>
+      <author>kamil@kbanc.com (Kamil Banc)</author>
+    </item>
+
     <item>
       <title>Google&apos;s Nano Banana Pro Is Finally Ready For Business</title>
       <link>https://kbanc.com/claims-library/google-nano-banana-pro-business</link>

public/sitemap.xml

@@ -2,19 +2,19 @@
 <urlset xmlns="http://www.sitemaps.org/schemas/sitemap/0.9">
   <url>
     <loc>https://kbanc.com/</loc>
-    <lastmod>2025-11-25</lastmod>
+    <lastmod>2025-11-27</lastmod>
     <changefreq>weekly</changefreq>
     <priority>1.0</priority>
   </url>
   <url>
     <loc>https://kbanc.com/claims-library</loc>
-    <lastmod>2025-11-25</lastmod>
+    <lastmod>2025-11-27</lastmod>
     <changefreq>weekly</changefreq>
     <priority>0.9</priority>
   </url>
   <url>
     <loc>https://kbanc.com/claims-library/all</loc>
-    <lastmod>2025-11-25</lastmod>
+    <lastmod>2025-11-27</lastmod>
     <changefreq>weekly</changefreq>
     <priority>0.9</priority>
   </url>
@@ -234,4 +234,10 @@
     <changefreq>monthly</changefreq>
     <priority>0.8</priority>
   </url>
+  <url>
+    <loc>https://kbanc.com/claims-library/job-title-means-nothing-to-ai</loc>
+    <lastmod>2025-11-26</lastmod>
+    <changefreq>monthly</changefreq>
+    <priority>0.8</priority>
+  </url>
 </urlset>

src/data/claims.ts

@@ -1366,6 +1366,42 @@ export const ALL_CLAIMS_DATA: ClaimData[] = [
     ],
     infographics: [],
     supportingContext: "The evaluation was conducted through a collaboration with AI strategist Mr V, who performed extensive stress-testing of Google\'s Nano Banana Pro API over a 12-hour period. The testing focused specifically on the tool\'s ability to generate professional product mockups, pitch deck visuals, and branded marketing materials—use cases that represent the fastest business applications for AI image generation. The methodology emphasized practical business scenarios where accurate text rendering and brand name display are critical for professional use, addressing the common failure mode of previous AI image tools that produce distorted or misspelled text on generated visuals.",
+  },
+  {
+    slug: "job-title-means-nothing-to-ai",
+    title: "Your job title means nothing to AI",
+    date: "2025-11-26",
+    featuredClaim: "AI requires workflows, not titles: decompose tasks into six components to unlock machine delegation",
+    description: "The article explores how professionals can effectively use AI by breaking down their work into specific, executable workflows instead of relying on abstract job titles. It provides a framework for translating complex tasks into machine-readable instructions that leverage AI\'s capabilities.",
+    keyPoints: [
+      "Job titles are meaningless to AI; workflows are what matter",
+      "Decompose tasks into trigger, inputs, transformation, decisions, output, and check",
+      "Become an architect of systems, not a passive user of AI",
+      "Strategic human judgment remains crucial in AI-assisted workflows"
+    ],
+    topics: [TOPICS.STRATEGY, TOPICS.TOOLS, TOPICS.IMPLEMENTATION],
+    claims: [
+      "Job titles like \'Project Manager\' provide AI with no actionable triggers, inputs, or decision logic whatsoever.",
+      "Effective AI delegation requires decomposing fuzzy tasks into six components: trigger, inputs, transformation, decisions, output, check.",
+      "Every workflow needs a concrete trigger event, not vague phrases like \'when needed\' or \'as things come up\'.",
+      "Decision logic for AI must use binary rules with hard thresholds, never subjective judgment or intuition.",
+      "Professionals who decompose workflows become system architects while others risk being replaced by those systems eventually."
+    ],
+    claimTitles: [
+      "Titles Are Meaningless",
+      "Six-Component Workflow Framework",
+      "Concrete Triggers Required",
+      "Binary Decision Rules",
+      "Architects vs Displaced"
+    ],
+    originalUrl: "https://aiadopters.club/p/your-job-title-means-nothing-to-ai",
+    quote: "The moment you can see your role as a collection of mechanical steps rather than a single abstract responsibility, you unlock something powerful.",
+    keyStatistics: [
+      { stat: "6 defined components", context: "Number of pieces required to make any workflow AI-ready: trigger, inputs, transformation, decisions, output, and check" },
+      { stat: "50 employees threshold", context: "Example strategic judgment decision point for categorizing inbound leads as high priority versus nurture status" }
+    ],
+    infographics: [],
+    supportingContext: "The article presents a systems decomposition methodology based on translating professional expertise into machine-executable instructions. The author demonstrates this through a practical example of lead response automation, showing how a vague task description transforms into explicit workflow components. The framework emphasizes maintaining human oversight through strategic threshold setting, template creation, and final review checkpoints. This approach positions professionals as system architects rather than task executors, preserving strategic judgment while delegating mechanical execution to AI agents.",
   }
 ];