SEO Automation Gone Wrong- Lisa Chen’s $18K Technical Audit Disaster | Interview

SEO Automation Gone Wrong- Lisa Chen's $18K Technical Audit Disaster SEO Automation Gone Wrong- Lisa Chen's $18K Technical Audit Disaster

SEO Automation Gone Wrong: Lisa Chen’s $18K Technical Audit Disaster

Lisa: Hello? Morgan?

Morgan: Hey! Yeah, I can hear you. Can you hear me?

Lisa: Barely. You’re super quiet. Can you— [static] —there, that’s better.

Morgan: Sorry, I’m using my AirPods and the battery’s dying. Let me switch to my phone. [rustling sounds] Okay, can you hear me now?

Lisa: Yeah, perfect. So what’s this about? You said something about technical SEO disasters?

Morgan: [laughs] Yeah. I heard through the grapevine that you built an AI audit tool that… how did someone describe it… “spectacularly fucked up a client site”?

Lisa: [long pause] Oh god. Who told you about that?

Morgan: I’m not gonna say. But they said you’d probably be willing to talk about it. Were they wrong?

Lisa: No, they weren’t wrong. I’ve actually been thinking I should talk about it publicly. Like, as a warning to other people. But it’s still embarrassing.

Morgan: Well, that’s kind of the whole point of these interviews. Real talk about real fuckups.

Lisa: [laughs] Okay. Yeah. Let’s do it. Where do you want me to start?

Morgan: Start with who you are and what you do.

Lisa: I’m Lisa Chen. I’m a Technical SEO Specialist— have been for about nine years now. I work at this agency called AuditFlow. We do technical audits for mid-to-large sized websites. E-commerce, SaaS, media companies, that kind of thing.

Morgan: And you built an AI tool?

Lisa: Yeah. Well, I built it with help. I’m not a developer, but I know enough Python to be dangerous. Which, in retrospect, is exactly the problem.

Morgan: When did you build it?

Lisa: I started in January 2024. We were getting slammed with audit requests and I was basically drowning. Like, a proper technical audit takes me 20-30 hours of work. Site crawls, backlink analysis, Core Web Vitals review, schema markup validation— it’s a lot. And we had this backlog of like 15 clients waiting.

Morgan: So you thought, let me automate it.

Lisa: Exactly. And it seemed smart at the time! Everyone was talking about AI agents that could do complex tasks. So I thought, what if I could build an agent that did the grunt work and I just reviewed its recommendations?

Morgan: What did the agent actually do?

Lisa: It would take in a domain, run Screaming Frog, pull backlink data from Ahrefs, grab Core Web Vitals from PageSpeed Insights, and then use Claude— the AI, not you— to analyze all that data and generate recommendations.

Morgan: That sounds… reasonable?

Lisa: It was reasonable! At least, I thought it was. I tested it on our own website first. The recommendations were good. Then I tested it on two client sites where I’d already done manual audits, and it caught like 80% of the same issues I’d found. I was so proud of myself.

Morgan: When did you use it on a real client?

Lisa: March. We had this client— B2B SaaS company, subscription management software. They’d been with us for like two years. Good relationship, lots of trust. They wanted a comprehensive audit before a big site redesign.

Morgan: And you ran your AI agent on them.

Lisa: Yep. Took about three hours instead of the usual 25. The agent generated this beautiful 47-page PDF report. Looked professional as hell. Color-coded issues by severity, specific recommendations for each problem, the whole nine yards.

Morgan: What did the report say?

Lisa: Lots of standard stuff. Some mobile usability issues, a few broken internal links, some schema markup that could be improved. And then at the end, there was this section on backlinks. The agent had identified 10,847 backlinks that it flagged as “low quality and potentially harmful” and recommended disavowing them.

Morgan: 10,000 backlinks?

Lisa: 10,847. And I remember looking at that number and thinking, “Wow, they have a lot of spammy links.” But I didn’t actually check them. I just… trusted the AI.

Morgan: Oh no.

Lisa: Oh yes. So I send the report to the client— guy named Tom, their VP of Marketing. And he’s like, “This is great, super thorough, let’s implement everything.” And I’m like, “Perfect, we can knock this out in two weeks.”

Morgan: Did you implement the disavow file?

Lisa: We did. Tom’s team handled most of the on-site stuff— the mobile issues, the broken links, whatever. But the disavow file, that was on us. So I took the list of 10,847 domains from the report, formatted it properly, and submitted it to Google Search Console on March 28th.

Morgan: When did you realize something was wrong?

Lisa: Not for three weeks. Three. Weeks. Because disavows take time to process, right? So I wasn’t expecting to see immediate changes. But in mid-April, Tom emails me and he’s like, “Hey, our traffic is down about 15% over the last two weeks. Is that related to the audit changes?”

Morgan: What did you say?

Lisa: I said it was probably just normal fluctuation. Which, in my defense, 15% fluctuation isn’t that unusual. But then a week later, he emails again. “We’re down 30% now. Something’s wrong.”

Morgan: What did you do?

Lisa: I panicked internally but stayed calm externally. I told him I’d investigate. So I logged into their Search Console and started digging through the data. And their rankings had just… collapsed. Like, pages that were ranking positions 1-5 for their main keywords were now at positions 15-25.

Morgan: Did you connect it to the disavow file?

Lisa: Not immediately. My first thought was that maybe Google had rolled out an algorithm update. So I checked all the SEO news sites, checked Twitter, asked in some SEO communities. But there was no update. Nothing had changed except the stuff we’d implemented.

Morgan: When did you figure it out?

Lisa: April 24th. I’m sitting at my desk at like 9 PM because I’ve been stress-investigating this for days, and I decide to actually look at the disavow file. Like, really look at it. Not just the number of domains, but the actual domains.

Morgan: And?

Lisa: And the third domain on the list was TechCrunch. The AI had recommended disavowing a backlink from TechCrunch.

Morgan: [pause] Oh my god.

Lisa: Yeah. And I keep scrolling. Forbes. Entrepreneur. The New York Times. Industry-specific trade publications. Every single high-authority backlink they’d earned over the years, the AI had flagged as “low quality and potentially harmful.

Morgan: Why? How did that even happen?

Lisa: I spent the next two days figuring that out. Turns out, the AI was using anchor text as its primary quality signal. And all these authoritative sites were linking to them with generic anchor text like “subscription management” or “learn more” or just their company name. The AI interpreted generic anchor text as a sign of a low-quality link.

Morgan: That’s… that’s insane.

Lisa: It gets worse. The AI also flagged any domain with a high spam score in Ahrefs as problematic. But “spam score” in Ahrefs is predictive, not definitive. And some of the domains had elevated spam scores just because they had a lot of external links, which is normal for news sites and media companies.

Morgan: So the AI basically disavowed all their best backlinks.

Lisa: Every. Single. One. Out of 10,847 disavowed domains, I’d estimate maybe 200 were actually spammy. The other 10,600+ were either neutral or actively beneficial. And the most beneficial ones— the authoritative, high-trust domains— got nuked.

Morgan: What did you tell Tom?

Lisa: [long exhale] I called him. Didn’t email, called. And I said, “I found the problem, and it’s my fault.” And then I explained what happened. And there’s just this silence on the phone for like 30 seconds.

Morgan: What did he say?

Lisa: He said— and I’ll never forget this— he said, “Lisa, I trusted you.” Not angry, just… disappointed. Which somehow felt worse.

Morgan: What happened next?

Lisa: We immediately removed the disavow file. Like, that day. But here’s the thing about disavows— removing them doesn’t instantly restore your rankings. Google has to recrawl your backlink profile, reprocess everything. It can take weeks or months.

Morgan: How long did it actually take?

Lisa: For their rankings to fully recover? About four months. But even after four months, they weren’t quite back to where they’d been. They plateaued at about 90% of their original traffic.

Morgan: Did they fire you?

Lisa: They didn’t fire the agency, but they did request a different account manager. I don’t blame them. And we refunded them for six months of services, which came out to about $18,000.

Morgan: Out of your pocket?

Lisa: No, the agency ate it. But it definitely affected my standing there. I didn’t get a bonus that year. And my boss made it very clear that this was a major fuckup.

Morgan: How did that feel?

Lisa: Awful. Like, I’d been so proud of building this AI tool. I thought I was innovating, being efficient, solving a real problem. And instead, I’d just… broken a client’s website because I was too lazy to check the AI’s work.

Morgan: Do you think you were lazy, or do you think you were trusting?

Lisa: [pause] Both? I mean, I trusted the AI because I wanted to trust it. Because if I could trust it, that meant I could do more work in less time. But I should have known better. I should have spot-checked the recommendations. I should have at least looked at a sample of those 10,000 domains before disavowing them.

Morgan: Did you tell anyone else at the agency what happened?

Lisa: Yeah, I had to. We did this whole post-mortem meeting where I walked everyone through what went wrong. And it was humiliating, but also necessary. Because other people were starting to experiment with AI tools too, and they needed to know the risks.

Morgan: What did you learn from that meeting?

Lisa: That AI is really good at following patterns, but really bad at understanding context. The AI saw “generic anchor text + elevated spam score = bad link” and just applied that rule uniformly. It didn’t understand that TechCrunch is authoritative even if the anchor text is generic. It couldn’t differentiate between a spammy blog network and a legitimate news site.

Morgan: Do you still use the AI audit tool?

Lisa: Hell no. I deleted it. Well, I archived it. But I don’t use it. And I went back to doing manual audits. Which sucks because I’m back to spending 25 hours per audit instead of 3.

Morgan: Do you use AI for anything in your work now?

Lisa: Yeah, but way more carefully. I use ChatGPT to write first drafts of audit reports. I use Claude to help me understand complex technical issues. But I don’t let AI make decisions anymore. It’s a research assistant, not a consultant.

Morgan: Has your relationship with Tom recovered?

Lisa: Not really. I reached out to him a few months after the whole thing to apologize again and see how they were doing. He was polite but distant. I think that bridge is pretty much burned.

Morgan: Do you feel like you were scapegoated?

Lisa: No. I mean, I’m the one who built the tool. I’m the one who didn’t check its work. I’m the one who submitted that disavow file. Nobody forced me to do any of that. So yeah, it was my fault.

Morgan: That’s pretty accountable of you.

Lisa: [laughs] What else am I going to do? Blame the AI? I built the AI. I chose to trust it. That’s on me.

Morgan: Have you warned other people about this?

Lisa: I try to, yeah. Whenever I see someone in a community talking about building AI tools for SEO, I’m like, “Cool, just make sure you’re checking its work.” Some people listen. Some people think I’m being paranoid.

Morgan: Do you think you’re being paranoid?

Lisa: No. I think I’m being realistic. AI is powerful, but it’s not infallible. And in SEO, one bad recommendation can destroy months or years of work. So yeah, be careful.

Morgan: What would you do differently if you could go back?

Lisa: [pause] I’d still build the tool, but I’d add a human review step. Like, the AI generates recommendations, and then I spend 2-3 hours reviewing them before they go into the report. That way I get the efficiency gains without the catastrophic risk.

Morgan: Why didn’t you do that the first time?

Lisa: Because I wanted to save time. Which is so stupid in retrospect. Like, what’s the point of saving 20 hours if you cause $18,000 in damages and lose a client’s trust?

Morgan: Fair point.

Lisa: Yeah. [pause] You know what the worst part is?

Morgan: What?

Lisa: I’m still tempted to automate things. Like, even after all this, I see a repetitive task and I think, “I bet I could build a script for this.” It’s like an addiction.

Morgan: Do you act on it?

Lisa: Sometimes. But now I test everything to death first. And I never, ever let AI touch anything related to backlinks without human review.

Morgan: Sounds like you learned your lesson.

Lisa: [laughs] Yeah. The hard way.

Morgan: Do you think other people are making the same mistakes you made?

Lisa: Oh, definitely. I see people on Twitter all the time talking about fully automated SEO workflows. And I’m just like, “Good luck with that.” Because eventually, something’s going to break. And when it does, they’re going to be in the same position I was— frantically trying to undo the damage while their client’s traffic crashes.

Morgan: What do you think the future of AI in SEO looks like?

Lisa: I think AI will be a copilot, not an autopilot. It’ll help you work faster, but you still need to be the one making decisions. Anyone who tries to fully automate SEO with AI is going to get burned, just like I did.

Morgan: That’s probably good advice.

Lisa: It’s advice I wish I’d followed before I broke a client’s site.

Morgan: [laughs] Well, at least you can warn other people now.

Lisa: Yeah. Silver lining, I guess.

Morgan: Alright, I should let you go. This was really helpful though. Thanks for being so honest about it.

Lisa: Thanks for not judging me too harshly.

Morgan: Hey, we’ve all made mistakes. Yours just had a bigger dollar amount attached.

Lisa: [laughs] Wow, thanks for that.

Morgan: [laughs] Sorry, I’m kidding. But seriously, thanks for talking through this. I think it’ll help people.

Lisa: I hope so. Alright, take care Morgan.

Morgan: You too, Lisa.

[end]


Key Lessons Learned

“AI is really good at following patterns, but really bad at understanding context.”

1. AI Can’t Replace Domain Expertise

Lisa’s AI agent correctly followed its programmed logic: generic anchor text + elevated spam score = bad link. But it completely missed the crucial context that TechCrunch, Forbes, and The New York Times are authoritative domains regardless of anchor text patterns.

2. Testing on Your Own Site Isn’t Enough

The AI tool worked well on AuditFlow’s website and matched 80% of Lisa’s previous manual audits. But those tests didn’t reveal the catastrophic blind spot in backlink analysis because they didn’t involve disavowing thousands of links.

3. Blind Trust in Automation Is Dangerous

“I should have at least looked at a sample of those 10,000 domains before disavowing them.”

Lisa saw “10,847 backlinks flagged” and trusted the number without spot-checking even a handful of examples. A 10-minute review would have immediately revealed the error.

4. The Numbers Looked Professional, But Were Wrong

The 47-page PDF report was beautifully formatted with color-coded severity levels and specific recommendations. Professional presentation masked fundamentally flawed analysis—appearance doesn’t equal accuracy.

5. Disavow Files Are Nuclear Weapons

Disavowing 10,847 backlinks—including every authoritative link the client had earned—caused a 50% ranking drop within three weeks. Even after removing the disavow file, full recovery took four months and plateaued at 90% of original traffic.

6. Speed Savings Don’t Justify Risk

Lisa reduced audit time from 25 hours to 3 hours—but caused $18,000 in refunds, months of recovery work, and a destroyed client relationship. The time savings were illusory because the cleanup cost far more.

7. AI Tools Need Human Guardrails

“I’d still build the tool, but I’d add a human review step. The AI generates recommendations, and then I spend 2-3 hours reviewing them.”

Automation should increase efficiency of human work, not replace human judgment entirely. The right approach: AI does the grunt work, humans make the final decisions.

8. Context Matters More Than Patterns

Ahrefs “spam scores” are predictive metrics, not definitive judgments. News sites and media companies often have elevated spam scores simply because they have many external links. The AI couldn’t distinguish between correlation and causation.

9. Client Trust Is Fragile

“Lisa, I trusted you” hit harder than anger would have. Two years of good relationship work evaporated in one phone call. Trust takes years to build and seconds to destroy.

10. Accountability Accelerates Recovery

Lisa immediately admitted fault, explained what happened, removed the disavow file same-day, and facilitated a $18K refund. While the client relationship didn’t survive, her professional reputation did because she owned the mistake completely.


About Lisa Chen

Lisa Chen is a Technical SEO Specialist with nine years of experience conducting comprehensive website audits for e-commerce, SaaS, and media companies. She specializes in large-scale site architecture optimization, backlink analysis, and Core Web Vitals implementation.

After discovering SEO through a college internship at a digital marketing agency in 2015, Lisa developed an obsession with the technical side of search—the crawl budgets, redirect chains, and structured data that most people find tedious but she finds fascinating. She taught herself Python to automate repetitive tasks and quickly became known as “the person who could fix anything technical.”

In March 2024, Lisa built a custom AI agent to automate technical audits, hoping to reduce her workload from 25 hours per audit to just 3 hours. The tool worked perfectly in testing—until it recommended disavowing 10,847 backlinks for a B2B SaaS client, including every authoritative link from TechCrunch, Forbes, and The New York Times. The client’s rankings dropped 50% within three weeks.

“I trusted the AI because I wanted to trust it. Because if I could trust it, that meant I could do more work in less time. But I should have known better.”

The disaster cost \$18,000 in refunded fees, destroyed a two-year client relationship, and forced a complete rethinking of how AI should be used in SEO work. Lisa spent four months helping the client recover to 90% of their original traffic, learning painful lessons about automation, context, and accountability.

She now advocates for AI as a “copilot, not an autopilot” in technical SEO work. She uses AI for report drafts and research assistance but maintains strict human review for all recommendations, especially anything involving backlinks. Her post-mortem presentation at AuditFlow became required viewing for the entire team.

Lisa lives in San Francisco and spends her free time rock climbing and teaching Python basics to other SEOs who want to automate responsibly.


This interview was conducted via phone call in June 2025. Lisa was candid about both her technical decisions and emotional responses throughout the crisis. The conversation has been edited for clarity, but her willingness to accept responsibility and warn others remains the core message.

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