Discussion Mistakes Best Practices

We made these 7 mistakes that killed our AI visibility - learn from our expensive lessons

LE
LearnedTheHardWay · Marketing Director
· · 189 upvotes · 12 comments
L
LearnedTheHardWay
Marketing Director · January 9, 2026

Let me save you the pain we went through. These mistakes cost us 6 months and significant budget.

Mistake 1: Treating it like keyword SEO We stuffed keywords. AI doesn’t care. Citation rate: 5%

Mistake 2: Ignoring author credibility Anonymous content everywhere. AI ignored us.

Mistake 3: Publishing thin content fast 50 pieces in 2 months. All useless. AI cited none.

Mistake 4: Not setting up monitoring Flew blind for 4 months. No idea what was working.

Mistake 5: Blocking AI crawlers Our robots.txt blocked Perplexity. Oops.

Mistake 6: Inconsistent entity info Different company descriptions everywhere. AI confused.

Mistake 7: Expecting immediate results Leadership got impatient at month 2. Program nearly cancelled.

What we do now (working):

  • Comprehensive topic coverage
  • Credentialed authors
  • Quality over quantity
  • Am I Cited monitoring from day 1
  • Clear AI crawler access
  • Consistent entity data
  • 12-month timeline expectations

Share your mistakes so others can learn!

12 comments

12 Comments

M
MistakesWeMade Expert GEO Consultant · January 9, 2026

I’ve seen all these mistakes and more. Let me categorize them.

Content mistakes:

MistakeWhy It FailsFix
Keyword stuffingAI reads meaning, not keywordsWrite naturally
Thin contentNothing unique to citeAdd original value
Duplicate/spunAI detects itCreate original
No structureHard to extractClear hierarchy

Technical mistakes:

MistakeWhy It FailsFix
Blocking crawlersAI can’t see contentCheck robots.txt
JS-only renderingMany AI bots don’t render JSUse SSR
Slow pagesCrawlers timeoutOptimize speed
Missing schemaEntity data unclearImplement markup

Strategic mistakes:

MistakeWhy It FailsFix
No monitoringCan’t improve blindSet up day 1
Scattered topicsNo authority builtFocus on clusters
Anonymous authorsNo credibility signalUse real experts
Short timelinePremature pivotPlan 12+ months

Every mistake has a pattern. Learn the patterns.

TF
TechnicalSEO_Fail · January 9, 2026
Replying to MistakesWeMade

The robots.txt mistake is more common than people think.

What we found:

Default WordPress security plugins often block:

  • PerplexityBot
  • ChatGPT-User
  • anthropic-ai
  • ClaudeBot

How to check:

# Test your robots.txt
curl https://yoursite.com/robots.txt

# Look for:
User-agent: PerplexityBot
Disallow: /

# This blocks Perplexity

The fix:

Explicitly allow AI crawlers:

User-agent: PerplexityBot
Allow: /

User-agent: ChatGPT-User
Allow: /

Our situation:

Blocked AI crawlers for 6 months without knowing. Zero Perplexity citations. Fixed robots.txt. Citations started within 2 weeks.

Check your robots.txt TODAY.

CL
ContentQuality_Lesson Content Director · January 9, 2026

The thin content lesson was expensive for us.

What we did wrong:

Hired cheap writers to produce 100 articles in 3 months. Each article:

  • 800-1,000 words
  • Generic information
  • No original data
  • Keyword focused

The result:

100 articles. 3 AI citations total.

What we do now:

20 articles in same timeframe:

  • 1,500-2,500 words
  • Original research/data
  • Expert authors
  • Comprehensive coverage

The new result:

20 articles. 12 AI citations (60% rate).

The math:

ApproachCostCitationsCost per Citation
Cheap/volume$10K3$3,333
Quality/focused$12K12$1,000

Quality is actually cheaper per outcome.

E
EntityMess · January 8, 2026

Entity inconsistency killed our AI visibility:

What we had:

  • Website: “XYZ Technologies, Inc.”
  • LinkedIn: “XYZ Tech”
  • Google Business: “XYZ Technology Solutions”
  • Wikidata: None
  • Schema: Missing

What AI saw:

“Are these the same company? Unclear. Don’t cite.”

The fix:

  1. Chose canonical name
  2. Updated all profiles
  3. Created Wikidata entry
  4. Implemented Organization schema
  5. Ensured sameAs connections

The impact:

Before: AI couldn’t identify us reliably After: AI recognizes us as single entity

Timeline:

Fix took 2 weeks. AI recognition improved within 6 weeks.

Check your entity consistency across:

  • Website
  • Social profiles
  • Business listings
  • Wikidata/Wikipedia
  • Schema markup
TR
Timeline_Reality Expert · January 8, 2026

The timeline expectations mistake is organizational:

What happens:

Month 1: “Let’s do AI visibility!” Month 2: “Why aren’t we appearing?” Month 3: “This isn’t working, cut budget”

The reality:

Month 1-3: Foundation building Month 4-6: First real visibility Month 7-12: Business impact

How to prevent:

Before starting, get alignment on:

  • 12-month minimum commitment
  • First 6 months = investment phase
  • Quarterly check-ins, not monthly pivots
  • Leading indicators (citations) before lagging (revenue)

Our presentation approach:

“AI visibility is infrastructure. Like building a factory, not running an ad. We’re building something that compounds.”

Set expectations early or fail fast.

MF
Monitoring_Fail Marketing Analytics · January 8, 2026

Not monitoring from day 1 is a critical mistake:

What we missed by not monitoring:

  1. Didn’t know what was working

    • Wasted budget on wrong content
    • Couldn’t double down on wins
  2. Didn’t see competitor movement

    • Competitor took over topics we could have won
    • Realized too late
  3. Couldn’t prove progress

    • Leadership lost confidence
    • Program nearly cancelled

Set up monitoring before creating content:

ToolPurposeWhen
Am I CitedAI citationsDay 1
GSCSearch dataDay 1
GA4Traffic patternsDay 1
Brand trackingSOVWeek 1

The cost of not monitoring:

We spent 4 months creating content without data. 60% of it was the wrong approach. That’s 60% wasted budget.

Monitor first, optimize second.

AC
Author_Credibility_Fail · January 8, 2026

Our author mistake was expensive:

What we did:

All content published as “Staff Writer” or “Marketing Team”

What happened:

8% citation rate across all content

What we changed:

Same content, added real author names with:

  • Credentials
  • LinkedIn links
  • Author pages
  • Schema markup

New results:

24% citation rate - same content, different authorship

The lesson:

AI evaluates WHO created content, not just WHAT is in it.

For YMYL topics:

The difference was even bigger:

  • Anonymous: 3%
  • Credentialed: 31%

Author investment pays off immediately.

L
LearnedTheHardWay OP Marketing Director · January 7, 2026

Amazing thread. Here’s the complete mistake prevention checklist:

Before Starting:

  • Set 12-month timeline expectations
  • Set up monitoring (Am I Cited)
  • Check robots.txt for AI crawler access
  • Audit entity consistency
  • Align on leading vs lagging indicators

Content Strategy:

  • Quality over quantity
  • Comprehensive topic coverage
  • Original data/research included
  • Clear structure with headers
  • Natural language, not keyword stuffed

Author Strategy:

  • Real author names
  • Credentials listed
  • Author pages created
  • Schema markup implemented
  • External profiles linked

Technical:

  • SSR or pre-rendered pages
  • Fast loading speeds
  • Schema markup complete
  • AI crawlers allowed
  • Entity data consistent

Ongoing:

  • Weekly monitoring review
  • Quarterly strategy assessment
  • Competitor tracking
  • Content iteration based on data

The meta-lesson:

Most mistakes come from applying old SEO thinking to new AI reality. AI isn’t keyword matching - it’s meaning matching.

Thanks everyone for sharing your expensive lessons!

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Frequently Asked Questions

What are the most common AI visibility mistakes?
Common mistakes include treating AI optimization like keyword SEO, ignoring author credibility, creating thin content, not monitoring AI visibility, blocking AI crawlers, inconsistent entity information, and expecting immediate results without proper investment.
How can AI visibility mistakes be avoided?
Avoid mistakes by focusing on comprehensive topic coverage instead of keywords, investing in author credibility, creating original research content, setting up AI monitoring from day one, ensuring technical accessibility, and setting realistic timelines.
What's the biggest mistake in AI search optimization?
The biggest mistake is applying old SEO tactics to AI visibility. Keyword stuffing, thin content, and link scheme thinking don’t work. AI systems evaluate meaning, authority, and trustworthiness differently than traditional search engines.

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