How to Optimize Content for ChatGPT & AI Search? | SEO vs LLM Optimization

What happens when someone asks ChatGPT about a brand, product, or topic — and how does an LLM decide what to mention or cite? I had a thoughtful conversation with Raja Jeevan Kumar Maduri, Product & AI Advisor for Retail, Commerce & Consumer Startups, about one of the biggest questions SEO and content professionals are facing today: Can we actually optimize our content to improve how AI systems understand, mention, and cite our brands? Raja explained the difference between traditional SEO and optimizing content for LLM-driven search, using a familiar SEO framework to explain the process. We discussed the 6 stages of optimizing content for machines: Discovery & Strategy Technical SEO / Foundation & Layout Content Creation Authority & Link Building for Trustworthiness Monitoring & Analysis Iteration Loop The conversation also touched on AI sentiment scores, machine-readable schema, identifying KPIs, writing specific content instead of relying only on hooks, building corpus data, and how tools and AI agents can support this process. There were several points in this conversation that were new to me — but once explained, they made a lot of sense. If you're an SEO, content, marketing or digital professional trying to understand AEO, GEO and the new AI search landscape, this conversation is worth watching. Guest: Raja Jeevan Kumar Maduri Product & AI Advisor – Retail, Commerce & Consumer Startups Guest:   / rajajeevankumar   Host:   / nareshkumarwriter   Official website: https://aimforseo.com/ LinkedIn:   / aim-for-seo   #llmseo #chatgptseo #answerengineoptimization #generativeengineoptimization #searchengineoptimization #seopodcast #digitalmarketing #aiseo #aiexpert #writer #seocontent