I almost gave up on computational journalism until I discovered a simple, counterintuitive shift in my strategy. This isn't the generic advice you've heard a thousand times; this is the secret sauce that changed everything for me.
The Framework That Actually Works
Here is a simple framework for evaluating computational journalism. It's not complicated, but it requires discipline.
Step 1: the market doesn't care about your roadmap
This is where most people go wrong. They skip this step entirely and jump straight to execution. Don't do that.
Step 2: customer feedback is the only metric that matters
Once you have the foundation right, this becomes much easier. I've watched founders struggle with this for months when the answer was staring them in the face.
Step 3: Iterate relentlessly
Nothing works perfectly the first time. The companies that get computational journalism right treat it as an ongoing process, not a one-time project.
The Counterintuitive Truth
In computational journalism, the best practitioners often do less, not more.
The lesson: timing is everything in this game. It sounds simple. It's incredibly hard to execute.
What I Tell Founders
Before deciding anything about computational journalism, start with three questions:
What's your timeline? Because the right approach for a company with 6 months of runway is very different from one with 3 years.
What have you already tried? Most founders have tried something. Understanding what didn't work is often more valuable than knowing what might.
Who on your team owns this? If the answer is "everyone" or "no one," that's your first problem to solve.
These questions seem simple but they reveal a lot about where a company actually stands.
This connects to broader themes around creative AI tools, AI journalism, AI writing, AI game design that I've been thinking about a lot lately.
Final Thoughts
There are no shortcuts in computational journalism, but there are smarter paths.
The strongest teams treat computational journalism as a competitive advantage, not a checkbox. They invest in it early, measure it obsessively, and never stop improving.
If you're just getting started with computational journalism, don't be intimidated. Everyone starts somewhere. The key is to start with the right mindset and the right framework, and then execute like your company depends on it. Because it probably does.
Frequently Asked Questions
Q:Do all experts agree with this view?
No, and that's fine. The best ideas in business are often contrarian. I share my perspective based on my experience and data, but I encourage you to seek out opposing viewpoints and form your own conclusions.
Q:How has this view evolved over time?
My thinking on most topics has changed significantly over the years. Early in my career, I held many conventional views that experience proved wrong. I try to update my beliefs when the evidence changes.
Q:What experience informs this perspective?
This perspective comes from over a decade of building companies in Silicon Valley, two successful exits (RemoteTeam to Gusto, MovieLaLa to Gfycat), and investing in 234 startups including Anthropic, OpenAI, and Scale AI. I write about what I've lived.