I build AI systems that automate SEO & business process at a scale that manual execution can't match. Leading AI & Automation at AT&T, shipping RAG pipelines, knowledge graphs, and programmatic SEO infrastructure across 50M+ pages. Not strategy decks. Production systems. What that looks like: AI integrations connecting LLMs to live SEO data for automated keyword research and content optimization. A RAG-powered internal linking engine using vector embeddings and entity recognition. Automated pipelines that run technical SEO audits at scale. A market share content tool with geo-segmentation that generates 3-year roadmaps. 10 years in Technical SEO, the fundamentals that power how Google ranks content today. Site migrations, crawl budget optimization, structured data at enterprise scale, Core Web Vitals, international SEO. Tools: Botify (50M+ crawls), Screaming Frog, Ahrefs, SEMrush, BigQuery, Python. Now I also build for what's next: Answer Engine Optimization, Generative Engine Optimization, AI Overviews. Google is evolving search, I'm building systems that evolve with it. Published: "Google, SEO and Helpful Content: How AI Can Be Helpful for E-Commerce Websites", Journal of Digital & Social Media Marketing, December 2024. Tags: SEO Lead, AI Product Owner, Technical Product Manager SEO: Technical SEO, Local SEO, SEO Migration, Schema Markup, AI: GEO, AEO, Ai search, MD files, LLMs.txt, Ai bot analysis, RAG, Graph, Internal link recommendations Content & Growth: Topical Clusters, Content gaps, internal linking's, Optimization or existing pages and New growth opportunities https://speakerdeck.com/venkatapagadala1 2026-09-17 02:30:49 -0400 User First, Algorithm Second puts customer needs, pain points, and intent at the center of SEO and AI search strategy. Through case studies and a personal car-buying journey, it shows how zero search volume can still hide real demand. The presentation explores 20 data sources including reviews, social communities, earnings calls, and research to uncover customer insights. It explains how to turn those insights into useful content, better products, and scalable AI workflows that build trust and drive growth. User First, Algorithm Second puts customer needs, pain points, and intent at the center of SEO and AI search strategy. Through case studies and a personal car-buying journey, it shows how zero search volume can still hide real demand. The presentation explores 20 data sources including reviews, social communities, earnings calls, and research to uncover customer insights. It explains how to turn those insights into useful content, better products, and scalable AI workflows that build trust and drive growth. Thu, 17 Sep 2026 00:00:00 -0400 https://speakerdeck.com/venkatapagadala1/industrial-context-graphs https://speakerdeck.com/venkatapagadala1/industrial-context-graphs