The Best Content Engine in the AI Age
You can just do things.
Organic content is one of the few high-ROI distribution channels left:
Product advantages can disappear overnight as a team of skilled engineers using AI can disrupt years of careful engineering. But a strong brand, built on trust and consistent storytelling, doesn’t vanish so easily. Even when companies or Founders stumble, audiences often rally around them because they’re relatable.
Every company needs a content strategy, and yet most companies think about content as an output problem: how many posts per week, what format, which platform. Equally important is the content engine, the underlying source of ideas, quality, and thematic distinctiveness that feeds everything downstream.
My thesis is that there’s a new type of content engine that AI enables and is heavily under-utilized.
There are a fixed set of Content Engines that can be applied to any business
Educational engines are the most common. Something new comes out, you break it down and explain it. If you’re a tax advisor, this makes perfect sense: you can respond to new regulations and guide people through unique situations and build trust in the process. The logic is clean. Unfortunately, while previously understanding something required a great deal of time, AI is getting better than this and more people are turning to ChatGPT for teaching them things.
Research engines go deeper. The McKinsey Global Institute is the content engine for the entire company. They staff entire teams on in-depth reports, publish headline studies, and then Partners globally would cascade that into more tactical tailored marketing.
Research engines can work at smaller scales too. If you’re a SaaS company, you could survey customers in your industry and publish trends.
Experiential engines are used by influencers. Do things, then talk about what happened. But this category doesn't just include latte photos and outfit-of-the-day posts.
My friend Hector rode a bicycle from the UK to Asia and blogged the entire amazing journey.
You could visit a conference and describe not just the panels but who you met, where you ate and what surprised you. Even in professional industries, people are hungry for the personal texture around otherwise dry insight.
Ultimately, each of these engines works pretty well but there's a fourth one that should be embraced more.
The rise of PROJECTS
Build something, then talk about it.
Indie Hackers were pretty early to this trend: developers like Pieter Levels build software projects in public, talk openly about their metrics and growth. The audience that cares about the process (other Indie Hackers) also tends to buy the products which means the products feed the content and the content helps grow the products.
But your “project” could be anything. PewDiePie has largely switched to a project-based content engine, taking us along his experiments with AI. A project could just be the chair you designed for your balcony, a book you finally finished, an open-source tool, a pop-up event, a film. The category is vast.
And project-based content is where AI creates the most leverage, for a reason that has nothing to do with content production. AI makes it dramatically easier to complete projects. The bottleneck for most people was never having ideas. It was finishing them.
I’m experiencing this firsthand. I started a research paper just after my son was born and never completed it. With AI, I’m empowered to push it across the finish line. It’s like having a collaborator with lesser intelligence (perhaps) but infinite energy and enthusiasm.
The ability to overcome procrastination and help drive things to completion is one of the genuinely positive outcomes of AI.
Project-based content wins
It forces creativity. The other three engines are easy to be rational about. Want educational content? Look at what questions people are asking and answer them. Research? Go a layer deeper on the same questions. Experiences? See what’s trending and do it.
But picking the right project requires genuine curiosity, ability and creativity. It’s unique to you.
It produces the most durable output. Educational content is transient. People may be interested in a new regulation only this quarter. A project or product can last far longer, become part of your portfolio, compound in ways that a how-to post never will.
It challenges you the most. Completing a project end-to-end may involve the combination of all the above: research, education, and new experiences. Because it’s harder, there’s also less people doing it.
It creates better psychological feedback loops. When you complete a project, the sheer achievement is motivating regardless of whether the content performs well. You still have the thing you built and ideas for what to do next. Compare that to doing research purely for content purposes: if the content doesn't “hit”, you may feel discouraged.
The content is secondary, which makes it better. Effortless content comes as a byproduct. When the project is the primary output, you avoid the death spiral of creating content for content’s sake. Your updates have substance because you’re actually doing something.
Project-based content engines are not for everyone
There are definitely some drawbacks to this approach.
Project timelines don’t always match content cadences. If you need to publish weekly but your project drags on for months, you can run dry on exciting updates. That mismatch can create a negative spiral where you feel like you’re not progressing fast enough, and the reduced marketing output becomes another source of pressure that wouldn’t exist if the project wasn't tied to your content schedule.
It doesn’t fit funnels. In a funnel/problem-oriented marketing model, a customer has a problem, you talk about the problem, you present the solution. They don’t particularly care about your story or side projects.
For that reason, project-based content is more natural for smaller brands. Of course some bigger brands do this really well and it works for them (e.g., Red Bull).
Finally, AI. AI is making project completion cheaper, which makes the project-based content engine, historically the most expensive and demanding to run, suddenly the most attractive.
If you’re a company, experiment with what “project” means beyond the obvious category of open source software. The space of possible projects is vast, and the cost of exploration has dropped dramatically.
And don't forget about quality. The brands that will stand out are ones that apply their taste & craft to their projects as much as they do their products.