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A framework for understanding how AI search builds on traditional SEO — and why the fundamentals matter more than ever. Every few years, someone declares SEO dead. Today, it's AI search that's supposedly killing it. After spending the last 60 days measuring my own brand's visibility across ChatGPT, Google AI Overviews, Claude, and Perplexity, I don't think that's what's happening. I think something more interesting is happening. Visibility has become more complex. This articl

This is Post 4 in a series documenting a live LLM visibility audit on my own brand, NextWise Studio. Post 1 covered the baseline. Post 2 covered what I changed and why. Post 3 covered the 30-day results. This post covers Day 60. Sixty days ago, I started asking a question I think more brands should be asking: If someone searches for what I do in an AI tool, do they find me? At baseline, the answer was no. Not for category searches — the kind where someone doesn't already know

This week, I received an inquiry through the contact form on my website. The message came from someone claiming to represent a well-known fashion brand. They were looking for support with CRM, email marketing, marketing automation, retention, and growth strategy. At first glance, it looked promising. As someone building a consulting practice, those are exactly the types of conversations I hope to have. But something felt off. The email domain didn't quite match the company's

This is Post 3 of 3 in a series documenting a live LLM visibility audit on my own brand, NextWise Studio. Post 1 covered the baseline. Post 2 covered what I changed and why. This post covers the 30-day results. Thirty days ago I set out to answer a simple question: if someone searches for what I do in an AI tool like ChatGPT or Perplexity, do they find me? At baseline, the answer was no. Not when it came to category searches, the kind where someone doesn't already know my nam

This is Post 2 of 3 in a series documenting a live LLM visibility audit on my own brand. Post 1 covered the baseline results. Post 3 will share the 30-day data. In my last post, I shared the results of auditing my own LLM visibility. The short version: strong brand recognition, zero category visibility. When someone searched for me by name, three out of four AI tools found me. When someone searched for what I do — without knowing my name — I didn’t appear once across twenty r

The hardest part of AI strategy isn’t the technology. It’s convincing anyone to fix what’s underneath before they’ve already failed. The real risk isn’t messy data. It’s losing your baseline. When teams hit data problems, messy inputs, misaligned definitions, unreliable signals, the instinct is to move forward anyway. New tools. New tracking. Cleaner schemas built from scratch. And honestly, I get it. Legacy data wasn’t designed for how we want to use AI today. Fixing it is s

This is Post 1 of 3 in a series documenting a live LLM visibility audit on my own brand. Post 2 covers what I changed and why. Post 3 will share the 30-day results. Sometimes the best way to build a methodology is to eat your own cooking first. It started with a client conversation. Someone came to me wanting help showing up better in AI search -- not just traditional rankings, but the answers people now see in ChatGPT, Perplexity, and Google's AI Overviews. It was the right

This is the final post in a short series on what actually matters as marketing AI moves from pilots to performance. And it is the hardest one to write, because this is where the tradeoffs stop being theoretical and start showing up in real work. I do not come at this from a creative director lens. I come at it from the place where creative, production, ops, and performance collide. And right now, that collision is getting louder. What I’m Seeing on the Ground Across teams I h

How AI-powered personalization, first-party data, and customer journey mapping are reshaping marketing in 2026 Personalization and even hyper-personalization are once again being positioned as the key to engagement and conversion. This time, the trend is right. Not because the idea is new, but because AI-powered personalization finally changes what is possible . In the past, personalization promised relevance but delivered complexity, burnout, and inconsistent results. In 202

Agentic AI is quickly becoming the new baseline for modern marketing teams. Planning agents. Creative agents. Targeting agents. Measurement agents. Across marketing, AI is being positioned as the next layer of orchestration that promises speed, coordination, and scale. In the right conditions, that promise is real. But based on years spent working inside complex marketing organizations, one pattern keeps showing up: teams that struggle with agentic AI are rarely blocked by th

For the last few years, the question leaders were asking was simple. Are we using AI? That question came from urgency, pressure, and a lot of noise. Teams ran pilots, tested tools, and automated tasks. They proved they could move faster. Now the question has changed. Teams are past asking whether they should use AI. The harder question is whether it is actually working. Not whether work is getting done faster or whether more campaigns are shipping, but whether any of it is cr

Efficiency is great. But it does not always create growth. After my last post, I found myself thinking more about the idea of efficiency. I said efficiency is great, but it does not automatically translate into growth. And that is true. Most marketers would love more time for strategy. More time to think, plan, and understand what is actually happening across the journey. But even when you get that time back, strategy still stalls if the data is unclear or scattered. That is

From automation to personalization — where the real growth lies. AI for Efficiency or Growth: What's the Trend? Recently, someone asked me: “Do you think companies today are using AI more for efficiencies or for data insights? Without hesitation, I said, efficiencies. It ’s the fastest, most measurable win: automate a task, trim a timeline, lower a cost. And to be clear, there’s nothing wrong with that. Efficiency matters. But I can’t shake the feeling that many teams are sto

A few days ago, I shared a late-night progress update on LinkedIn about how I used AI to turn seven detailed startup playbooks into one unified Agile master backlog. That post sparked a wave of curiosity. Founders, PMs, and marketing leaders all wanted to know how I did it. What prompts did I use? How did I structure the playbooks? And how did AI help without taking over the strategy? Those questions inspired this follow-up and the creation of a new Human-in-the-Loop Toolkit

My Initial Worry Over the past few years I have been leaning on AI tools to help me brainstorm, refine, and validate ideas for multiple...

MIT just reported that 95% of corporate AI pilots fail to deliver measurable impact. TechRadar says U.S. companies have poured billions...

When I logged into Claude recently, it popped up a new feature: “Want to connect your apps for deeper personalization?” On the surface,...

If you're using AI for client deliverables, strategic planning, or building it into your workflows, you've probably learned that the real...

Lately I've noticed a lot of discussion on LinkedIn about using AI for writing. There's a real struggle between AI-generated expertise...

The marketing world is obsessed with AI prompt engineering right now. Every day, my LinkedIn feed fills with "the perfect prompt for X" and "10 ChatGPT hacks that will transform your workflow." But after spending the past year integrating AI into everything from go-to-market strategy to customer lifecycle design, I've realized we're focused on the wrong thing. The real opportunity isn't perfecting individual prompts—it's developing strategic fluency that adapts based on your