Month: September 2026

  • You Ask, I Answer: AI vs Human Service Tiers?

    Summary In today's episode, I tackle Beatrice's question about whether marketing agencies should split their AI-driven services from their human-driven premium offerings or treat AI as invisible infrastructure. Here's what this means for you. Hourly billing models collapse when AI shrinks six hours of work to six minutes, so you must shift to value-based pricing…

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  • Good Times Buy Ideas, Bad Times Buy Action: What Marketing and Sales Leaders Need to Know

    When times are good, people buy ideas. When times are bad, people buy action. When times are good, people buy strategy. When times are bad, people buy tactics. When times are good, people buy brand. When times are bad, people buy price. When times are good, people buy growth. When times are bad, people buy…

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  • You Ask, I Answer: Blocking Adversarial AI Scrapers?

    Summary In today's episode, I break down how to defend your website against competitors who deploy AI agents to scrape your pricing pages and summarize your gated content for countermarketing. Here's what this means for you. You can build layered bot defenses that turn cheap, automated scraping into a resource-draining dead end so adversaries give…

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  • Almost Timely News: 🗞️ Advice I Would Give to a New PR Practitioner (2026-09-06)

    _Almost Timely News: 🗞️ Advice I Would Give to a New PR Practitioner (2026-09-06) :: View in Browser_ The Big Plug ✍️ Enroll in my new course, AI for Writers and learn how to make AI write better. Content Authenticity Statement 99% of this week’s newsletter was made by me, the human. You will see…

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  • Why Locally Run Open Weights AI Models Are More Trustworthy Than ChatGPT and Claude

    “Do we really trust Chinese models that much?”” Lisa asked that question in the Trust Insights Analytics for Marketers Slack group and the short answer is, “we really trust models under our control that much”, which means open weights models, models we download and run on our own hardware or in trusted inference providers. Here’s…

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  • So What? Examining AI Writing Styles of Different AI Systems

    Summary In today's episode, I examine the writing styles of major AI systems and reverse engineer which one writes most like a specific human author. Here's what this means for you. You gain a framework for fingerprinting your own writing with Python metrics so you can pick the AI model that sounds closest to you.…

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  • You Ask, I Answer: Generative vs Agentic SEO Strategy?

    Summary In today's episode, I explain the difference between generative answer optimization and agentic SEO, and walk through what companies must do to prepare their websites for AI agents acting on behalf of users. Here's what this means for you. You can future-proof your web presence by adopting Web MCP, which simultaneously improves accessibility for…

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  • Why Creators Should Automate AI Inputs, Not Outputs

    As a creator, thinker, or knowledge worker: Use AI to automate your outputs, and you’re likely to get weaker. Use AI to automate your inputs, and you’re likely to get stronger.

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  • You Ask, I Answer: Feeding Customer Feedback to LLMs Safely?

    Summary In today's episode, I walk through how to safely feed unstructured customer feedback like reviews and support tickets into language models to extract marketing insights without compromising data privacy. Here's what this means for you. You'll get a clear three-step approach that protects sensitive customer data while still letting you mine feedback for actionable…

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  • The AI Pay Cut: Why 10x Productivity Isn’t Raising Your Salary

    AI is a pay cut for you, the human. It’s tempting to take the easy route and talk about a stagnant job market, or tech companies using AI as a cover for large scale job cuts, but that’s not what I’m talking about here. A decade ago, Katie Robbert and I worked at a PR…

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