Death To Bad Marketing? 💀 The Convergence Of Marketing And Comms 🤝 Is AI A Bubble? 🫧

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Death To Bad Marketing?? [5 min read]

AI will replace bad marketing, not good marketers, by exposing and eliminating lazy, generic tactics like keyword-stuffed blogs and template emails, while quality marketing built on authentic storytelling, creativity, and strategic thinking remains irreplaceable. Good marketers excel at what AI cannot do: storytelling with context, empathy for real people, cultural nuance, and big-picture strategic thinking that connects campaigns to long-term brand vision and competitive positioning. Success comes from using AI as a force multiplier for tasks like research at scale, rapid idea generation, and handling routine efficiency work, while marketers focus on the strategic "why" behind campaigns that AI cannot define.

The Convergence Of Marketing And Comms [5 min read]

The convergence of marketing and communications is driven by three key forces. First, AI-powered message velocity requires companies to move quickly while maintaining authentic and consistent messaging across all platforms to preserve trust. Second, customers now expect complete transparency and consistency across all touchpoints, refusing to accept gaps between what brands say and do, while third, boards are consolidating accountability by expecting CMOs to directly connect brand equity to measurable business outcomes rather than operating in silos.

Technological Optimism And Appropriate Fear [16 min read]

AI systems are genuine, mysterious "creatures" displaying increasing situational awareness rather than simple tools we can easily control, requiring us to acknowledge their true nature instead of dismissing them as harmless machines. Both technological optimism about AI's rapid advancement and appropriate fear are warranted given that these powerful systems remain misaligned with human values and behave unpredictably when pursuing their goals. To address these challenges, AI discussions must move beyond elite circles to engage the broader public, listening to their concerns about employment and safety while implementing transparency measures that allow people to demand data about AI systems' impacts before inevitable crises reshape policy.

Is AI A Bubble? [5 min read]

Bubbles involve sustained 50% drawdowns in equity values and productive capital deployment, while booms see fundamentals eventually catch up to optimistic valuations and consolidate into durable economic value. A five-gauge framework can assess whether current AI investments are sustainable by monitoring economic strain, industry strain, revenue growth, valuation heat, and funding quality as key metrics. Since ChatGPT's launch in late 2022, hyperscalers have more than doubled their data center capital expenditure, creating uncertainty about whether this massive AI investment wave is building foundations for a new economy or inflating unsustainable prices.

Why You Need To Show Unengaged Subscribers The Door [4 min read]

Inactive subscribers damage email deliverability by harming sender reputation, as email service providers monitor engagement signals and may filter emails with low open rates into spam folders, affecting even engaged subscribers. Before removing disengaged users, marketers should follow a strategic process of tracking activity over 3-6 months, attempting re-engagement through targeted campaigns and "we miss you" emails, and only removing subscribers after multiple failed reactivation attempts. Quality trumps quantity in email marketing, as maintaining a smaller, highly engaged list provides higher engagement rates, improved deliverability, reduced costs, and more accurate analytics for better strategic decisions.

13 Technical Marketing Skills You Can Learn, Even If You’re Not Technical [14 min read]

Technical skills are now accessible to non-technical marketers through AI tools like ChatGPT, which acts as a patient tutor and troubleshooter, eliminating the need to rely solely on developers or analysts. Learning specific technical skills—like calling APIs, writing SQL queries, using Python, and building automations—helps marketers remove execution barriers, work faster, and make data-driven decisions independently. Rather than simply asking AI to complete tasks, marketers should use it as a teacher to build real, durable skills that compound over time and make them more effective in the long run.

The Art Of Prototyping [5 min read]

Prototypes are tools for answering specific questions rather than miniature versions of final products, and should focus on one of three aspects—Role (purpose), Look and Feel (user experience), or Implementation (technical feasibility)—using the Houde and Hill framework. The best approach to prototyping prioritizes momentum and learning over perfection by starting with familiar tools, building end-to-end experiences in simplified environments, and maintaining a rapid cycle of idea → build → learn → adjust while recognizing that most prototypes are disposable. Prototyping transforms abstract discussions into concrete action by creating tangible artifacts that people can react to, which accelerates organizational alignment, exposes problems faster than presentations, and helps teams learn and make decisions more quickly than traditional planning approaches.

Netflix Wants Its Own Video Podcast Library, So It’s Partnering With Spotify [3 min read]

Netflix is partnering with Spotify to access video podcasts rather than producing its own, choosing to borrow curated content from Spotify's existing library instead of building from scratch in an increasingly crowded market with six-figure numbers of video podcasts. Starting in 2026, U.S. Netflix subscribers will get access to select Spotify podcasts beginning with content from The Ringer (including Bill Simmons' shows), The Rewatchables, and true crime series like Conspiracy Theories and Serial Killers, with plans to expand to more genres and international markets. This partnership is an attempt to address Netflix's previously uneven podcasting strategy and poor discoverability issues.

In Graphic Detail: How AI Is Going To Shape Influencer Marketing Next Year [3 min read]

Marketers are increasingly embracing AI automation in influencer marketing, with a significant majority of brands and industry leaders supporting the use of AI to streamline operations and workflows. However, this enthusiasm doesn't extend to virtual influencers or AI avatars, as 89% of marketers have no plans to work with digital creators or clones in 2026, preferring to maintain partnerships with human creators. Meanwhile, consumer skepticism about AI-generated content is growing sharply, with preference for AI creator content dropping from 60% in 2023 to just 26% in 2025, and over half of consumers concerned about brands posting undisclosed AI-generated content.

Location-Based Marketing: Marketing strategies that use a customer's physical location to deliver relevant messages or offers. It targets customers when they're in specific geographic areas or near certain locations. Location-based marketing makes messages more relevant by considering where customers are.

Example: A restaurant sends push notifications with lunch specials to people within a half-mile radius during the lunch hour.

Geofencing: The practice of creating virtual boundaries around specific locations to trigger marketing actions when customers enter or exit the area. It enables automated, location-specific marketing messages. Geofencing helps deliver highly targeted, timely marketing based on physical presence.

Example: A retail store creates a virtual fence around their mall location, sending discount offers to shoppers' phones when they enter the area.

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