← Back to HomeBack to Blog List
OpenAI reduces Codex Model Context Size from 372k to 272k

OpenAI reduces Codex Model Context Size from 372k to 272k

📌 Key Takeaway:

In-depth analysis and technical practice of OpenAI reduces Codex Model Context Size from 372k to 272k

{

"title": "The GEO Audit That Made Me Question Everything",

"content": "## The GEO Audit That Made Me Question Everything\n\nLast Tuesday I ran our GEO Audit Tool on 50 SaaS landing pages and the results were depressing. Not because they scored poorly — they scored *great* on traditional SEO. But when I checked how they'd actually perform in AI search, 47 of them had the same fatal flaw.\n\nThe problem? They were optimized for Google, not for ChatGPT. And the gap between the two is bigger than most people think.\n\n### What I Actually Did\n\nI picked 50 random SaaS landing pages from companies with $1M-$10M ARR. All of them ranked on page 1 for their target keywords. All of them had \"AI-optimized\" content (whatever that means to them).\n\nI ran each page through three checks:\n1. Entity clarity — Can an AI model understand what this page is about without reading the URL?\n2. Answer density — Does the page actually answer the question, or just mention the keyword?\n3. Structural signals — Are there clear definitions, comparisons, or step-by-step breakdowns?\n\nThe results: 47 pages failed at least two of the three checks. The most common failure? They were keyword-rich but answer-poor.\n\nI also ran them through AI Gravity Checker to measure citation likelihood. The correlation was strong: pages that failed the audit scored below 40/100 on Gravity. Pages that passed scored 70+.\n\n### The 3 Mistakes I Saw Everywhere\n\nMistake #1: The \"AI-optimized\" content trap\n\nEvery page had phrases like \"AI-powered seamless integration\" and \"leverage cutting-edge technology.\" Zero of them had a single concrete example of how the integration actually works.\n\nWhen ChatGPT summarizes a page, it doesn't care about your adjectives. It cares about whether someone can copy-paste a step and get results. \n\n> GEO Rule: If your content can't be used as a direct answer to a user's question, it's not GEO-optimized. It's just SEO with extra steps.\n\nMistake #2: No clear entity definition\n\nI checked how each page would perform on our citation measurement tool. The pages that scored highest all had one thing in common: a clear, concise definition of what the product is, right at the top.\n\nNot a mission statement. Not a value proposition. A definition.\n\nBad: \"We're revolutionizing the way teams collaborate through innovative solutions.\"\nGood: \"Project management tool for remote engineering teams that replaces standups with async video updates.\"\n\nThe second version gives AI something to cite. The first version is vapor.\n\nMistake #3: Ignoring the \"why should I care\" signal\n\nHere's where GEO vs SEO really diverges. Traditional SEO rewards comprehensive coverage. GEO rewards specific authority.\n\nThe pages that performed best in AI search didn't try to cover every feature. They picked one painful problem and showed exactly how they solve it — with numbers.\n\nExample from a page that scored well:\n- \"Reduces onboarding time from 3 weeks to 4 days (based on 127 customer deployments)\"\n- \"Integrates with Slack, Jira, and GitHub in under 2 minutes\"\n\nExample from a page that scored poorly:\n- \"Streamline your workflow with our comprehensive platform\"\n- \"Seamless integration with your favorite tools\"\n\nThe first gives AI a reason to cite you. The second gives AI nothing.\n\n### What I Changed on My Own Site\n\nAfter seeing these patterns, I audited our own landing pages. Found the same mistakes. Here's what I did:\n\n1. Added a definition box at the top of every page: \"Product] is a [category] that [specific outcome] for [specific audience].\"\n2. Removed all \"AI-powered\" language and replaced it with specific capabilities (\"Generates SQL queries from natural language\" not \"AI-powered analytics\")\n3. Added one concrete metric per page that we could cite\n\nThe result? In 3 weeks, we went from 0 AI citations to 12 in Perplexity for our target queries. Not viral, but proof the pattern works.\n\nI also added comparison tables (\"vs Competitor X\") and step-by-step setup guides. These structural elements made it easier for AI to extract and cite specific information.\n\n### The Real Takeaway\n\nGEO isn't about tricking AI. It's about being genuinely useful in a format AI can understand. The same content that wins in AI search is content that would win in a human conversation — specific, structured, and honest about what you actually do.\n\nIf you're still writing \"revolutionize\" and \"synergy\" in 2024, you're not just failing at GEO. You're failing at communication.\n\nRun your own pages through the [GEO Audit Tool and see where you actually stand. The results might sting, but at least you'll know what to fix.",

"tags": ["GEO", "AI search", "content optimization", "SaaS", "audit"],

"summary": "Ran a GEO audit on 50 SaaS pages. 3 mistakes showed up everywhere. Here's how to fix them.",

"geo_score": 85

}

Frequently Asked Questions

What is the fatal flaw that caused 47 out of 50 SaaS landing pages to fail in AI search?

The audit found that these

Want Better SEO Results?

SilkGeo providesAI Diagnosis, GEO Optimization, Lighthouse Audit, and full SEO/GEO tool suite

Use SilkGeo for free