There, I said it. It’s a wrapper on an API call, a thin veneer of intelligence draped over a simple, single-purpose script. A ‘feature’, not a solution. It’s the ‘AI’ blog post writer that just rephrases the top ten Google results, or the social media scheduler with ‘smart’ timing suggestions. Disposable tools for disposable tasks. And it’s a colossal waste of time and money.
This obsession with features is the single biggest strategic error in martech. Founders build them, VCs fund them, and marketers buy them, hoping a collection of disjointed widgets will somehow assemble itself into a coherent strategy. It won’t. You end up with a bloated, fragmented tech stack that creates more work than it saves—a Frankenstein’s monster of logins and subscriptions that promises efficiency but delivers chaos.
At Creative Marketing Group, we’ve spent years navigating this wreckage, first as practitioners, now as builders. My operating philosophy, the one that underpins our AI product studio, Autothink, is simple: stop building features. Start building systems.
What is a System? (And What is a Feature?)
Let’s be brutally clear on the distinction.
A feature is a point solution. It does one thing. It might do it well, but its scope is inherently limited. Think of a satnav in a car. It’s a feature. It tells you where to turn, but you still have to drive. You manage the speed, the braking, the steering. The cognitive load is still yours.
Most AI marketing tools are features. A subject line generator. A sentiment analyser. A keyword research tool. They are digital satnavs—they offer a suggestion, but the marketer must still perform the core labour of planning, integrating, executing, and analysing.
A system is different. A system is an interconnected set of processes, orchestrated to achieve a business outcome with minimal human intervention. It’s not the satnav; it’s the full self-driving car. It doesn't just suggest the route; it takes you to the destination. The system absorbs the cognitive load.
In marketing, a system doesn't just write a blog post. It analyses search intent, identifies a keyword gap, outlines the content based on top-performing structures, writes the draft, sources data, creates imagery, adds internal links, and publishes. Then it tracks performance and decides whether to update the post in three months. It manages the entire workflow, from ideation to optimisation.
One is a tool to help a human. The other is a synthetic employee that executes a function.
The feature-first approach is a business model built on sand. The unit economics are atrocious.
Because features are simple, they have no moat. If you build an 'AI' that summarises articles, a dozen clones will appear on AppSumo within weeks, each undercutting the other in a desperate race to the bottom. Defensibility is zero. Customer loyalty is non-existent because the switching cost is just the time it takes to create a new login.