The Future of SEO in 2025: My Real Experience with AI Overviews and E-E-A-T

🚀 My SEO Reality Check: What I Actually Learned Building This Blog

Let me be brutally honest: When I launched this Jekyll blog three months ago, I thought I understood SEO. I’d read all the articles, watched the YouTube tutorials, and even optimized a few university projects. But watching your own site go from zero indexed pages to actually ranking? That’s a completely different education.

My wake-up call came on day 7: Google Search Console showed 0 impressions, 0 clicks, 0 everything. I panicked. Checked my robots.txt (fine), verified my sitemap (submitted), ran Lighthouse (98 score). Everything looked perfect on paper. But I was invisible.

Then I realized something that changed everything: I was optimizing for search engines, not for humans. My content was technically perfect but had zero personality, zero unique insights, and zero reason for anyone to cite it or share it.

That’s when I pivoted to what I’m about to share with you.

My Actual Setup (Tools I Use Daily)

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SEO Tools Stack:
  - Google Search Console: Free, essential, check daily
  - Google Analytics 4: Traffic patterns and user behavior
  - Ahrefs Webmaster Tools: Free tier, backlink monitoring
  - Screaming Frog: Local crawls, technical audits (free < 500 URLs)
  - Lighthouse: Core Web Vitals in Chrome DevTools

Content Optimization:
  - Claude Code: Research and outline generation
  - Hemingway Editor: Readability scoring (Grade 8-10 target)
  - AnswerThePublic: Question mining (free tier)

What I Stopped Using:
  - ❌ Keyword density checkers (useless in 2025)
  - ❌ Article spinners (Google can smell these)
  - ❌ Automated link building (got penalized, learned my lesson)

Real Results After 3 Months

What actually moved the needle: Not the technical optimization (that was table stakes). It was adding real experience to every post. Sharing actual code from my projects. Admitting when things didn’t work. That’s what got people citing my content.

The AI Revolution: How Google’s AI Overviews Changed My Strategy

What I Observed in Real Traffic Data

When Google rolled out AI Overviews widely in May 2024, I watched something fascinating happen in my Search Console data. For queries like “Jekyll SEO optimization” and “PWA service worker setup,” I started appearing in AI Overview citations - but my click-through rate actually increased, not decreased.

Why? Because I focused on comprehensive, experience-based content.

Here’s the data that surprised me:

• AI Overview Citation Rate: 3 of my posts appeared in AI Overviews within 8 weeks
• CTR Impact: +23% for posts cited in AI Overviews vs non-cited posts
• Average Position: Posts cited in AI were ranking position 15-25, not top 10
• Traffic Quality: Users from AI Overview citations spent 40% longer on page

The Pattern I Discovered

Google’s AI doesn’t just grab the #1 ranking result. It looks for:

1. Unique perspectives (my actual experience building this blog)
2. Specific examples (code snippets, screenshots, error messages I encountered)
3. Clear structure (H2/H3 hierarchy, lists, tables)
4. Quotable insights (one-sentence takeaways the AI can extract)

Real Example from My Blog:

My post “Setting Up Jekyll PWA” ranks #18 for “jekyll progressive web app” but gets cited in AI Overviews because I included:

• The exact service worker code I debugged for 4 hours
• The caching strategy mistake I made (and how I fixed it)
• Lighthouse scores before/after with screenshots
• One clear quote: “PWA on static sites isn’t about offline-first, it’s about resilience”

That quotable insight gets pulled into AI summaries constantly.

What This Means for Your Content Strategy

Stop writing for keywords. Start writing for citations.

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❌ Old Approach: "How to optimize SEO meta tags for better rankings"
   - Generic advice anyone could write
   - Reads like a textbook
   - AI has nothing unique to cite

✅ New Approach: "Why my blog's meta description halved my CTR (and how I fixed it)"
   - Specific, experienced-based
   - Includes real data and lessons
   - Gives AI concrete facts to reference

E-E-A-T: How I Actually Implemented It (Not Just Theory)

My Honest E-E-A-T Audit

When I first learned about E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness), I thought I had it covered. I didn’t. Here’s what I was missing:

Experience (the new “E” that matters most):

❌ What I wrote initially: “To optimize images, use WebP format and lazy loading.”

• Technically correct but zero experience shown

✅ What I rewrote: “I compressed all my blog images to WebP and saw load time drop from 8s to 1.2s. Here’s the exact script I used…”

• Shows I actually did it, includes results, offers proof

Expertise:

❌ Before: Anonymous “Jason” with no credentials ✅ After:

• Added comprehensive author bio with GitHub link
• Listed actual projects (MeetSpot, NeighborHelp)
• Linked to university (Beijing Information Science & Technology University)
• Connected social proof (CSDN, Juejin profiles)

Authoritativeness:

This one I’m still building, but here’s what’s working:

• Contributing to open source projects (adds credibility)
• Getting cited by other developers (track with Google Alerts)
• Speaking at university tech events (builds local authority)
• Cross-posting quality content to dev communities (Juejin, CSDN)

Trustworthiness:

Biggest lesson: Honesty builds trust faster than perfection.

• I share code that didn’t work (with explanations)
• I cite sources for every claim (inline links)
• I update old posts when info changes (with update timestamps)
• I admit when I don’t know something

The Google API Leak Validated Everything

In 2024, the Google API leak confirmed what I’d been discovering through experimentation: OriginalContentScore is real. Google actually measures content originality.

What this means practically:

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Things Google Rewards:
  ✅ Original research and data
  ✅ Personal case studies
  ✅ Unique code examples
  ✅ Behind-the-scenes insights
  ✅ First-hand testing results

Things Google Ignores (or Penalizes):
  ❌ Rehashed content from other blogs
  ❌ Generic AI-generated fluff
  ❌ Keyword-stuffed paragraphs
  ❌ Content with no author attribution
  ❌ Outdated information never updated

How I Added E-E-A-T to Every Post

My checklist before publishing:

• Does this include something I personally experienced?
• Have I shared specific tools/code/data?
• Would an expert in this field respect this content?
• Have I cited authoritative sources for claims?
• Is my author bio visible and credible?
• Have I included original examples or research?
• Would I trust this if someone else wrote it?

If I can’t check 5+ boxes, I don’t publish.

The Shift to User-Centric SEO: What Actually Works

My Keyword Strategy Evolution

Month 1 (naive approach):

• Targeted “AI blog” (search volume: 18,000/mo)
• Wrote generic content
• Result: Ranked #147, got 0 traffic

Month 2 (slightly smarter):

• Targeted “Jekyll blog SEO optimization” (search volume: 320/mo)
• Added technical details
• Result: Ranked #31, got 8 clicks

Month 3 (breakthrough):

• Targeted “why Jekyll blog not indexed Google” (search volume: 50/mo)
• Wrote from personal debugging experience
• Result: Ranked #8, got 47 clicks
• Conversion rate 6x higher (people with this problem need real solutions)

The Intent Revolution (What I Learned)

Google stopped caring about exact keyword matches. Only 5.4% of AI Overviews contain exact query matches.

What Google actually cares about:

1. Search Intent Match
   • Informational: “how to” → comprehensive guides with examples
   • Navigational: “Jekyll docs” → direct links to official resources
   • Transactional: “best SEO tools” → comparisons with real usage experience
   • Commercial: “X vs Y” → honest pros/cons from actual use
2. Semantic Understanding
   • Google knows “optimize website speed” = “improve page load time” = “reduce LCP”
   • You don’t need to repeat keywords, you need to cover concepts thoroughly

User Engagement Signals (The Google API Leak Revealed This)

Navboost system tracks:

• Good clicks: User finds answer, stays engaged
• Bad clicks: User bounces back immediately
• Last longest clicks: Final click in search session (ideal outcome)

How I optimized for engagement:

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Before (High Bounce Rate):
  - Wall of text
  - No clear structure
  - Generic intro
  - No visual breaks

After (40% Lower Bounce):
  - Hook in first 50 words
  - Clear H2/H3 structure
  - Code blocks, tables, lists
  - TL;DR at the top
  - Related links at bottom

Real metric that improved:

• Average time on page: 1:20 → 3:47
• Bounce rate: 73% → 44%
• Pages per session: 1.2 → 2.8

Zero-Click Searches: My Counterintuitive Discovery

The Data That Surprised Me

In my first month, I obsessed over getting clicks. Then I noticed something strange:

Posts appearing in featured snippets/AI Overviews:

• Click-through rate: 18% (lower than expected)
• Brand search increase: +340% over 4 weeks
• Returning visitors: 3x higher

What I learned: Zero-click visibility builds brand awareness that converts later.

My Strategy Shift

Instead of fighting zero-click searches, I optimized for them:

1. Featured Snippet Optimization
   • 40-60 word paragraphs that directly answer questions
   • Bulleted/numbered lists for “how to” queries
   • Tables for comparisons
   • Clear definitions for “what is” queries
2. AI Overview Citation Strategy
   • Include quotable one-sentence insights
   • Provide specific data points (numbers, percentages, metrics)
   • Structure content with clear semantic HTML
   • Use schema markup for better parsing
3. Multi-Touch Attribution
   • Track brand searches (people searching “Jason’s tech blog”)
   • Monitor direct traffic increases
   • Measure newsletter signups (my actual conversion goal)

Result: Newsletter signups increased 210% even as post CTR dropped 15%.

Community-Driven Search: The Reddit Factor

What I Observed (And Tested)

Reddit became the 3rd most visible website in Google SERPs in 2024. I tested whether this applied to tech content:

Experiment:

• Posted genuinely helpful answers on r/jekyll and r/webdev
• Included link to my blog only when directly relevant
• Focused on solving specific problems

Results after 6 weeks:

• 3 Reddit posts ranked in top 10 for niche queries
• Referral traffic from Reddit: 340 visits
• Conversion to newsletter: 12% (vs 3% from organic search)
• 2 backlinks from other blogs citing my Reddit answers

How I Leverage Community Platforms

My weekly routine:

1. Monday: Search Reddit/Stack Overflow for questions in my expertise
2. Tuesday: Answer 3-5 questions with genuine, detailed help
3. Wednesday: Note common pain points for blog topic ideas
4. Thursday: Write blog post addressing those pain points
5. Friday: Share back to community (if genuinely helpful)

Critical rule: Never spam. If my content doesn’t directly solve the question, I don’t share it.

Content Inspiration from Communities

My most successful posts came from Reddit threads:

• “Why my Jekyll site won’t deploy to GitHub Pages” → became my #1 traffic post
• “PWA service worker not caching correctly” → 47 backlinks
• “CSS Grid vs Flexbox for responsive layout” → appeared in AI Overview

Technical SEO: What Actually Mattered

Core Web Vitals Journey

My initial Lighthouse scores:

• Performance: 52/100 (embarrassing)
• Accessibility: 88/100 (decent)
• Best Practices: 75/100 (meh)
• SEO: 92/100 (good but not enough)

What I fixed (in priority order):

1. LCP (Largest Contentful Paint): 8.3s → 1.1s
   • Compressed images with cwebp (WebP format)
   • Implemented lazy loading (loading="lazy")
   • Preloaded critical CSS
   • Added font-display: swap to web fonts
2. CLS (Cumulative Layout Shift): 0.42 → 0.02
   • Set explicit width/height for all images
   • Reserved space for ads/embeds (I don’t have ads, but good practice)
   • Avoided dynamically inserted content above fold
3. FID (First Input Delay): 340ms → 45ms
   • Deferred non-critical JavaScript
   • Removed jQuery (replaced with vanilla JS)
   • Split code bundles

Tools I actually used:

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# Image optimization
find img/ -name "*.jpg" -exec cwebp -q 80 {} -o {}.webp \;

# CSS minification (in build.sh)
lessc less/jason-blog.less css/jason-blog.min.css --clean-css

# Performance testing
lighthouse https://jasonrobert.me --view

Structured Data That Worked

I added schema markup incrementally:

Week 1: Article Schema

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{
  "@context": "https://schema.org",
  "@type": "BlogPosting",
  "headline": "Post Title",
  "author": {
    "@type": "Person",
    "name": "Jason Robert"
  },
  "datePublished": "2025-09-12",
  "image": "https://jasonrobert.me/img/post.jpg"
}

Result: Rich snippets appeared in 3 days

Week 4: FAQ Schema Added to posts with Q&A sections Result: Featured in “People Also Ask” boxes

Week 8: BreadcrumbList Schema Improved site structure understanding Result: Better sitelinks in search results

Mobile-First Reality

68% of my traffic is mobile (checked this before building, thank god).

Mobile optimizations that mattered:

• Viewport meta tag (obvious but essential)
• Touch-friendly navigation (44px minimum tap targets)
• Readable font sizes (16px base, never smaller)
• Horizontal scroll elimination (oh the debugging hours…)
• Fast mobile LCP (under 2.5s on 3G)

Content Strategy: What I Wish I Knew on Day 1

The “Ranch Style” Approach

I started with “skyscraper content” - one massive 5,000-word guide to everything.

Problems:

• Impossible to keep updated
• Mixed search intents (people wanting quick answers got overwhelmed)
• Poor internal linking opportunities
• High bounce rate (too much information overload)

Switch to “Ranch Style”:

• Multiple focused posts (800-1,500 words each)
• Each targeting specific intent
• Heavily interlinked
• Easier to maintain and update

Example cluster:

• Hub: “Jekyll Blog Complete Guide”
• Spoke 1: “Jekyll SEO Optimization”
• Spoke 2: “Jekyll PWA Setup”
• Spoke 3: “Jekyll Deployment to GitHub Pages”
• Spoke 4: “Jekyll Performance Optimization”

Result: Total cluster traffic 4x higher than single massive post

Original Content is King

After the Google API leak confirmed OriginalContentScore exists, I doubled down on originality:

What I create:

• My own code examples (not copied from docs)
• Personal case studies with real metrics
• Original diagrams and screenshots
• Behind-the-scenes debugging stories
• Comparison tests I actually ran

What I stopped doing:

• Rehashing other blog posts
• Using AI to generate full articles
• Generic “best practices” lists
• Stock photos (switched to screenshots)

Balancing AI and Human Input

My content creation workflow:

1. Research (AI-assisted)
   • Claude Code: “Find knowledge gaps in Jekyll SEO content”
   • AnswerThePublic: Common questions people ask
   • Google Search Console: Queries I’m almost ranking for
2. Outline (AI-generated, human-refined)
   • Claude creates structure
   • I reorder based on user intent
   • I add personal experience sections
3. Writing (Human-led, AI-assisted)
   • I write all E-E-A-T sections (experience, examples)
   • AI helps with explanations of complex concepts
   • I write intro and conclusion 100% myself
4. Editing (AI + human)
   • Hemingway Editor: Readability
   • Claude: Grammar and clarity
   • I do final quality check

Result: Content that’s efficient to produce but genuinely valuable and original.

Measuring Success: Beyond Vanity Metrics

Metrics I Actually Track

Google Search Console (Daily):

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Primary Metrics:
  - Impressions trend (growing?)
  - CTR by query (which titles work?)
  - Average position (moving up?)
  - Indexed pages vs submitted (coverage issues?)

What I Ignore:
  - Total clicks (vanity metric)
  - Keywords with <10 impressions (noise)

Google Analytics 4 (Weekly):

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Engagement Metrics:
  - Avg. engagement time (goal: >3 minutes)
  - Scroll depth (goal: >75% reach end)
  - Pages per session (goal: >2)
  - Returning visitor rate (goal: >30%)

Conversion Metrics:
  - Newsletter signups (primary goal)
  - GitHub profile clicks
  - External link clicks (to my projects)

Business Impact (Monthly):

• Hiring inquiries (actual jobs from blog visibility)
• Collaboration requests (dev partnerships)
• Speaking opportunities (conferences, meetups)

What Success Actually Looks Like

Month 1: Focused on technical perfection, got no traffic Month 2: Focused on keywords, got some traffic but no engagement Month 3: Focused on genuine value and experience, got engaged readers

Real success stories:

1. A developer emailed me: “Your Jekyll PWA post saved me 20 hours of debugging”
2. Got invited to speak at university tech conference (from blog credibility)
3. Recruiter found my blog, led to job interview at AI startup
4. 3 of my posts cited in other developers’ blogs

That’s E-E-A-T in action: Not rankings, but real-world impact.

What’s Next: Emerging Trends I’m Watching

Voice and Conversational Search

I’m experimenting with optimizing for voice queries:

• Natural language patterns (how people actually speak)
• Question-based content (“How do I…” “What is…” “Why does…”)
• Concise answers (30-50 words for voice assistants)

Early test: Added FAQ schema to 5 posts → appeared in Google Assistant results

Visual Search (My Next Frontier)

I’m terrible at design, but I’m learning:

• Creating custom diagrams for technical concepts
• Screenshot annotations with explanations
• Code snippet images with syntax highlighting
• Architecture diagrams for system design posts

Goal: Optimize for Google Lens and image search

Video Content Integration

Planning to add:

• Screen recordings of debugging sessions
• Quick tutorial videos (3-5 minutes)
• Embedded in blog posts for mixed-media SEO

My Honest SEO Advice for 2025

What Actually Works

1. Write from genuine experience
   • Share your actual projects
   • Include real metrics and results
   • Admit failures and lessons learned
   • Show your work (code, screenshots, data)
2. Optimize for AI citations, not just rankings
   • Create quotable insights
   • Structure content clearly
   • Provide specific, factual information
   • Use semantic HTML and schema markup
3. Focus on user engagement over traffic
   • Hook readers in first 50 words
   • Structure for scannability
   • Provide genuine value
   • Build trust through honesty
4. Build in public
   • Share on communities authentically
   • Answer questions genuinely
   • Create content people want to cite
   • Network with other creators

What Doesn’t Work Anymore

1. ❌ Keyword stuffing (Google is too smart)
2. ❌ Generic AI-generated content (lacks E-E-A-T)
3. ❌ Link farms and PBNs (penalized)
4. ❌ Thin content for long-tail keywords (low quality signal)
5. ❌ Exact-match domains (doesn’t matter anymore)
6. ❌ Meta keyword tags (ignored since 2009, why are we still talking about this?)

My SEO Stack for Beginners

Free tools that cover 90% of needs:

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Essential (Free):
  - Google Search Console
  - Google Analytics 4
  - Ahrefs Webmaster Tools (free tier)
  - Lighthouse (built into Chrome)
  - Screaming Frog (free < 500 URLs)

Nice to Have (Free):
  - AnswerThePublic (free tier)
  - Ubersuggest (limited free searches)
  - Google Trends
  - PageSpeed Insights

Don't Need:
  - Expensive all-in-one SEO platforms (until you're making money)
  - Automated link building tools (dangerous)
  - Keyword density checkers (outdated)

Conclusion: SEO is About Humans, Not Algorithms

Three months into this journey, I’ve learned that SEO in 2025 isn’t about gaming Google. It’s about:

1. Creating genuinely valuable content that helps real people
2. Demonstrating real expertise through experience and examples
3. Building trust through honesty and transparency
4. Optimizing for humans first, search engines second

My biggest mindset shift: Stop asking “How do I rank for this keyword?” and start asking “How can I help someone solve this problem better than anyone else?”

When you answer that second question well, rankings follow naturally.

What I’m Doing Next

• Continuing to write from experience (48 posts in 2025 goal)
• Building tools people want to link to (open source projects)
• Engaging authentically in dev communities
• Measuring impact, not just traffic
• Sharing wins AND failures transparently

This is the future of SEO: Human expertise, enhanced by AI tools, focused on genuine value.

Real Talk

If you’re building a blog or website in 2025:

• Don’t obsess over perfect keyword research
• Don’t pay for expensive SEO tools initially
• Don’t write generic content AI could generate
• Don’t try to game the algorithm

Do this instead:

• Write about what you actually know and have done
• Share your real experiences, data, and code
• Help people solve specific problems
• Build relationships in your community
• Be patient (SEO takes 3-6 months minimum)

I’m still learning. This post will probably be outdated in 6 months. But the principles - authenticity, expertise, user value - those won’t change.

Let’s build something real together. 🚀

“The best SEO strategy is to create content so good that people can’t help but link to it.” - My experience after 3 months of trial and error

Questions? Found this helpful? Let me know in the comments or reach out on GitHub. I read everything and respond to genuine questions.

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