Control group: a two-hour roadmap review meeting. Six people in a room (virtual). We debated features. We argued about timelines. We discussed dependencies. We left feeling productive.
Test group: We fed the same roadmap into Claude. No slides. No politics. No one trying to protect their pet project. Just the raw plan. The prompt: "Analyze this roadmap. Identify the three most likely failure points. Use first principles reasoning. Assume we will follow your recommendations without ego. If you need more data, ask for it."
A study from UNSW Sydney tracked content similarity across 388 keywords in 2019 and again in 2024. Content has become significantly more homogeneous. AI-generated pages now dominate the top rankings, but they all look and sound alike
"If the humans are not involved anymore, what does this mean for the industry in the future?" asked Professor Thomas Reutterer, who led the research.
A Graphite/Common Crawl analysis found that 86% of articles ranking high on Google Search are human-written. AI-generated content gets more impressions, but people still do not engage with it the way they engage with human-written content .
I believed that "keyword density" mattered. I spent hours making sure our target keyword appeared exactly 3-4 times per 500 words. I used tools that highlighted which words were "under-optimized." I even re-wrote paragraphs to squeeze in one more mention.
Turns out that hasn't been a real ranking factor for over a decade. Google's RankBrain (2015) and BERT (2019) made keyword density obsolete. These models understand context, synonyms, and user intent. They don't need you to say "best CRM for small business" five times. They know that "top CRM for startups" means the same thing.
What actually matters is topic coverage. Does your page answer the question completely? Do you cover related subtopics that a user would expect to see? Do you use natural language that matches how people actually ask questions?
At Google I/O 2026, the company announced the most sweeping set of changes to Search in over 25 years. The shift is conceptual as much as it is technical: traditional search waits for you to show up with a question. Information agents operate continuously in the background, reasoning across information to find what you need at the right moment
Here is what changed and why it matters for your brand.
1. Search now works while you sleep
Google introduced information agents, persistent background processes that monitor the web on your behalf and surface relevant findings without being asked . Described as the next evolution of Google Alerts, these agents do not just match keywords. They synthesize data from multiple sources, explain why a development matters, compare competing perspectives, and deliver actionable takeaways .
Last week, two search engines took very different positions on Generative Engine Optimization.
Google (May 15, 2026): GEO is "still SEO." No chunking. No llms.txt. No paid mentions. No special schema.
Bing (Fabrice Canel, April 2025): "Traditional SEO practices become obsolete." Bing added GEO to its official guidelines and built a dashboard inside Webmaster Tools to track Copilot citations.
At first glance, they seem to contradict each other. They are not.
The code works. The design sings. Customers who find you, love you.
But here's the problem AI will never just know.
Unlike Google, which crawls everything and figures it out eventually, AI learns from patterns. And if your product doesn't fit those patterns, you simply don't exist.
We were drowning in data. Page views. Session duration. Bounce rate. Time on site. New users. Returning users. Feature adoption. Support tickets. NPS scores.
None of it told us who was about to leave.
We had retention data. We had churn data. But it was backwards. You only knew someone churned after they cancelled. By then, it was too late.
So we looked for a leading indicator. One metric that predicted churn before it happened.
