{"slug": "ai-in-the-wild-confident-wrong-and-weirdly-expensive", "title": "AI in the wild: Confident, wrong, and weirdly expensive", "summary": "An SEO expert caught Google's Gemini providing incorrect technical advice about Shopify canonical URLs and search penalties, while the same AI model nearly cost the user $3,000 by wrongly diagnosing a Jeep SRT rear differential failure. The three separate Gemini conversations within one week demonstrate that large language models can deliver polished, convincing answers that are factually wrong, with the potential to cause financial harm when users lack domain expertise to challenge the responses.", "body_md": "[SEO](https://searchengineland.com/library/seo) »\n\n# AI in the wild: Confident, wrong, and weirdly expensive\n\n## AI doesn’t need to be fully correct to sound convincing. Three Gemini conversations reveal why expertise and skepticism still matter.\n\nImagine working in SEO for years, researching a problem you know inside and out, only to have an LLM confidently explain why your experience is *wrong*.\n\nThat happened to me. Actually, it happened three different times last week with Gemini.\n\nThe scary part wasn’t that the answers were obviously bad. It was that they sounded good. The responses were polished, believable, and directionally accurate enough that most people would never question them.\n\nAnd if you aren’t deeply familiar with the topic, you probably wouldn’t know how to challenge the answer.\n\nFunny enough, I caught it twice. The third time cost me money. All within the same week.\n\n## Example 1:* *Gemini educates me on technical SEO\n\nLet me give you some context.\n\nI’m currently helping migrate a client’s FAQ hub from a provider-hosted subdomain to a self-hosted implementation.\n\nThe FAQ lives under a /faq/ folder, but individual Q&A pages are parameter-based URLs. Normally not an issue… except Shopify forces canonicals back to the root /faq/ page, effectively preventing those pages from being indexed.\n\nWhile researching Shopify-specific solutions and duplication considerations, Gemini gave me this response:\n\n**Excuse me?!**\n\nYou will absolutely **not** be penalized for conflicting SEO signals.\n\nAt best, Google indexes what it wants. At worst, it ignores directives it doesn’t trust.\n\nThe bigger issue is the wording.\n\n“Penalty” is basically the magic word in SEO. The moment leadership hears it, priorities shift, momentum dies, and recommendations become harder to implement.\n\nThen Gemini doubled down.\n\nI asked whether removing the canonicals and allowing the parameter pages to exist independently was an option.\n\nGemini responded:\n\n- “Google generally ignores query parameters.”\n\n**Wow… just wow.**\n\nBelow is an implementation I worked on with the Saatva team, where we intentionally indexed parameter URLs within the shopping experience.\n\nSearch Console and URL inspection confirmed those pages indexed just fine.\n\nParameter pages can absolutely rank, index, and generate value.\n\nThe problem isn’t that Gemini was wrong *(as in it’s a more difficult implementation)*.\n\nIt’s that the answer sounded believable enough that someone without SEO experience would probably accept it and move on.\n\n## Example 2: Gemini says solve the issue with a $3,000 part\n\nThis one hit differently because I’m not a mechanic.\n\nI’ve been troubleshooting an issue on my Jeep SRT and spent hours outside in the sun collecting data, testing fuses, reviewing OBD2 logs, and trying to narrow down the root cause. After reviewing everything, Gemini confidently concluded the issue was likely a rear differential failure and suggested a full replacement.\n\nEstimated damage? Roughly **$3,000 in OEM parts alone.**\n\nThe response sounded fantastic. It was detailed, logical, and even complimented my troubleshooting process.\n\nThe problem? **It was wrong. Really wrong.**\n\nAfter pushing back and sharing additional OBD2 data I had been tracking during diagnosis, Gemini completely reversed course and admitted it jumped to a worst-case scenario without enough evidence.\n\nIn other words, I almost spent thousands replacing parts I didn’t need.\n\nThat’s what makes these examples interesting. In SEO, I immediately knew Gemini was wrong because I had years of experience to challenge the recommendation. Here, I didn’t have that advantage. I had to rely on skepticism, continue testing, and avoid treating the answer as fact.\n\nSame AI. Same confidence. Completely different outcome.\n\n## Example 3: Gemini cost me $20 million dollars!\n\nOK, technically, this was video game money.\n\nI was playing Madden, working through team logistics, and trying to optimize salary cap spending to re-sign key players and keep the roster together.\n\nAt some point, I got lazy and tagged in my partner, Gemini. I shared a screenshot of the team finances and asked for a roadmap to restructure contracts and optimize the cap situation.\n\nGemini gave me a detailed plan. I followed it.\n\nAnd it put me $20 million over the salary cap.\n\nThe funny part is this perfectly mirrors the earlier examples.\n\nThe answer looked good. It was organized, confident, and gave me a clear player-by-player action plan.\n\nSo I trusted it. Then I called Gemini out.\n\nYou’ll notice in the second screenshot that Gemini essentially points out that [I blindly trusted the recommendation](https://www.seoforlunch.com/p/blind-trust) without validating the math.\n\n**Honestly… fair.**\n\nThe difference is that this mistake only cost me fake money and a Madden franchise. The Jeep example almost cost me real money, and the SEO example could have cost implementation momentum and trust.\n\nThe value of expertise was never memorizing answers. It was knowing when something feels off, asking better questions, and recognizing when the answer smells like bullshit.\n\nAI didn’t remove that skill. If anything, it made it more valuable.\n\nAI isn’t replacing experts. It’s replacing people who have stopped thinking.\n\n*Contributing authors are invited to create content for Search Engine Land and are chosen for their expertise and contribution to the search community. Our contributors work under the oversight of the editorial staff and contributions are checked for quality and relevance to our readers. Search Engine Land is owned by Semrush. Contributor was not asked to make any direct or indirect mentions of Semrush. The opinions they express are their own.*", "url": "https://wpnews.pro/news/ai-in-the-wild-confident-wrong-and-weirdly-expensive", "canonical_source": "https://searchengineland.com/ai-wrong-expensive-479131", "published_at": "2026-06-04 13:00:00+00:00", "updated_at": "2026-06-04 15:17:38.656353+00:00", "lang": "en", "topics": ["large-language-models", "generative-ai", "ai-tools", "ai-ethics", "artificial-intelligence"], "entities": ["Gemini", "Shopify", "SEO"], "alternates": {"html": "https://wpnews.pro/news/ai-in-the-wild-confident-wrong-and-weirdly-expensive", "markdown": "https://wpnews.pro/news/ai-in-the-wild-confident-wrong-and-weirdly-expensive.md", "text": "https://wpnews.pro/news/ai-in-the-wild-confident-wrong-and-weirdly-expensive.txt", "jsonld": "https://wpnews.pro/news/ai-in-the-wild-confident-wrong-and-weirdly-expensive.jsonld"}}