This Process is a Mess
I live for people explaining how they approach analysis and critique. I desperately want to know how other people think about things so I can learn to think in new ways.
I want a compelling intellectual or journalistic project, but I also want to know how it was conceived and executed. I can’t help it. I’m a nerd.
Here’s the kind of thing I’m talking about. Verge reporter Mia Sato made a TikTok last year explaining one of her marquee articles, all about luxury product dupes. She explained how she connected the flood of copycat versions of a particular athleisure designer's skort to online content trends and developments in intellectual property litigation. Sato's writing and analysis are so smart, and yet wildly shareable—two qualities that rarely come together in today's media ecosystem.
So insights on her process? Yes, please!
Call me extremely biased, but I believe that analysis and critique are essential skills in the 21st-century economy. I also believe that communicating our analysis and critique is crucial to building buy-in with colleagues or clients, attracting audiences for our ideas, or advancing our agendas. In many ways, our success—defined just about any way you like—depends on our ability to make sense of what’s happening and communicate that to others.
Analysis and critique are skills that resist efficiency and optimization. Thinking about and communicating the underlying causes or context of a phenomenon almost always involves fits and starts. We can't force the discovery of oblique connections between phenomena. It takes time and experimentation to find the right metaphor or framing narrative to explain those connections.
Setting out to think about the world and share your findings entails making a mess. Probably a big one.
Still a Mess
Case in point, the essay I originally wanted to share with you today is still a mess. It's an analysis of the Washington Post layoffs in early February. Something I've been working on since early February. It's about how institutional infrastructure creates the necessary downtime for quality knowledge and creative production—and why all those WaPo journalists can't just turnaround and "go independent." It's a defense of organizations in an increasingly fractured (self-)employment landscape, as well as a call to independent workers and business owners to think about the infrastructure that their work depends on.
I'm going to give myself another week to tidy up that mess.
In the meantime, in the spirit of sharing the behind-the-scenes of the messy critical and analytical process I love (even when it's not loving me back), I decided to share a case study I delivered in the last session of Making Sense.
In this case study, I detail how an essay I wrote last year, "Drifting Toward the Status Quo," came together—from its inciting "Wait, what?!" moment to experimenting with different mental models to landing on an argument and completing the piece. On the podcast, you can hear the case study as I delivered it live. Below is a very cleaned up written version broken down into a loose set of “steps.”
No matter what kind of communicator, analyst, critic, or sensemaker you are, I hope you find something that makes you think a little differently the next time you have an idea to share.
By the way, the next session of Making Sense starts March 24. It's an 8-week live workshop series designed to guide you through this messy yet essential process for communication in the 21st-century economy. Click here for all the details.
Step 1. The "Wait, What?!" Moment
I had the "Wait, what?!" moment that led to this essay while listening to the October 10, 2025, episode of The Vergecast. This is the flagship podcast of tech news and analysis site, The Verge. I love the Verge for exactly the reasons this episode illustrates: they're people who love technology but don't put up with the bullshit in the industry.
This episode featured a conversation with their AI reporter, Hayden Field, who detailed all the news coming out of OpenAI's big conference, Dev Day. As I listen to Field explain the features OpenAI has announced, I can't help but think they are ridiculous. The co-hosts of the pod seem dubious as well.
Notably, the features that incite the biggest reaction from me are new app integrations within ChatGPT. Now, I can "chat" my way through a Zillow search or "request" a hoagie for delivery via DoorDash without taking a break from my AI boyfriend.
It felt stupid. It felt unstrategic. It felt like "the worst parts of consumer capitalism all rolled up into a big artificial intelligence poop sandwich."
My confusion, my anger—these were signs of my "Wait, what?!" moment. And yes, I get worked up about weird things. It was a feeling of internal chaos at a seemingly nonsensical set of information.
In this particular situation, some of the things that ran through my head sounded like, "Why do these products feel so stupid? Who wants this, let alone needs this? Why does a company worth $500 billion bother with this stuff when its purported vision is so much grander?"
Now this was a "Wait, what?!" moment for me. But I also knew I wanted to share my thoughts with my audience. So I needed to relate that "Wait, what?!" moment to them, connect it to something unexpected or confusing to them (that's you). While I follow AI news pretty closely, most of my audience doesn't. But the basic contours of my "Wait, what?!" moment are recognizable to all sorts of knowledge and creative workers today. So I knew there was an essay there.
Step 2. Stream of Consciousness
At that point, I finish my run and the podcast episode, and eventually get to work. I had a bunch of reactions to this "Wait, what?!" experience, and I decided to sit down and see what happens if I just dump it out into a document.
So that morning, in an hour or two, I got out around 800 words of what I would call raw material. Just thoughts. No structure, no real strategy, no argument or thesis behind it. I didn't know what I was writing. I had a vague idea of where I thought I wanted to go with it.
While I brain-dumped, I thought the piece I would write would be something about systems thinking, something about looking at the whole system to better understand what problems you actually want to solve or what problems need solving.
My thesis was going to be something like, "Look at these fools. There goes OpenAI solving problems that people don't have, because the only thing they can think to do with their venture capital is to steer it into banal consumer capitalism." Some of that language made it into the final piece, but that framing did not.
Step 3. Look for the Invisible Information
Phenomena are rarely nonsensical. Instead, they are nonsensical for my perspective or from your perspective. Given the right information (even if that information is wrong or misguided), the phenomenon in question will make sense. So when I’m making sense of a “Wait, what?!” moment, I want to figure out what information I’m missing (if I’m making sense for me) or you’re missing (if I’m making sense for you).
In this case, OpenAI was making business moves that seemed nonsensical to me. But I assume they make sense to OpenAI. There is some logic, set of beliefs, or mental model that makes it make sense.
Why does it make sense to the OpenAI team to roll out app integrations within ChatGPT? It could be a few things. First, they want to get investors excited about the billions of dollars that they've poured into the company. Second, they've been talking about agenticAI for a year now and have made very little progress on it, at least in the consumer sphere. This is something that evokes agentic AI without actually being agentic AI. Third, they love a hype cycle.
Because this was a project that involved first making sense of something for myself and then making sense for my audience, I needed to also look for invisible information on my side of the equation. What critical frameworks, beliefs, or mental models do I have that my audience might not?
Step 4. Taking a Break
All of that initial thinking and very rough writing happened on the same day I listened to the podcast episode. That was a Friday and, while I often write through the weekend, I took a full two days away from my computer. Though, of course, I kept thinking.
Step 4. Change of Course
When I came back to my shitty first draft, I had doubts about my initial framing. I wanted to broaden the framing to avoid writing yet another piece about AI. I wanted to ensure that this was going to be as helpful, relevant, and recognizable to my audience as possible.
I revisited one of critiques of OpenAI’s product moves from the podcast episode, namely that it seemed Sam Altman and Co were throwing spaghetti at the wall to see what stuck. And that spaghetti throwing seemed to be their whole business strategy.
Spaghetti throwing is not a business strategy. It is, in fact, a lack of strategy. Strategy is a filter for decision-making. It’s a productive constraint on available options.
Of course, we all have experience with throwing spaghetti at the wall. It’s a recognizable pattern, one that seems like it should work… but rarely (if ever) does.
Okay, so lack of strategy is an extremely common problem. Not only in well-funded tech companies, but also in the kind of businesses that many people in my audience (hello again, that’s you!) run. It’s also something that probably everyone has some experience with. I mean, who among us haven’t worked a job that was made more difficult by a lack of strategy among management?
Lack of strategy is also a problem that I have a mental model for: the air sandwich. I learned this mental model from Nilofer Merchant’s book The New How. Essentially, a company has an air sandwich when the executive team has mission, vision, and values sorted, the on-the-ground workers have execution sorted, but there’s no strategy tying those things together. There’s nothing in place to ensure that execution helps to get the company where leadership wants it to go.
To recap, I went from a systems-oriented message about finding the right problem to solve on October 10 to having a leadership and operations-oriented message about lack of strategy on October 13.
I spent most of that week building out that argument and got a draft to, say, 70% of the way there. But there were still too many ideas. The framing wasn’t wrong but it wasn’t the right framing, either.
Step 5. Fall Back on Structure
When I feel like I have a strong start to a piece but too many ideas vying for attention, I get out my pen and paper. I don’t know why this works best long-hand, but it does.
I jot down the “Wait, what?!” moment and my core argument. And then I list the various “beats” that support my argument. What would make this argument make sense? What would make this situation make sense? I don’t include anything that maybe I find interesting but isn’t necessary to support my argument. I do this from memory rather than going back to what I’ve written. I find this gives me the cleanest result.
At this point, I start fixating on the connection between strategy and the cliche that you can do anything if you work hard at it. My kid is a high school senior, and I’ve been exposed to a lot of BS axioms in the last six months. I thought that maybe I could start there, tie it to strategy, and then also talk about, to my mind, the bonkers business plan that OpenAI had embarked on.
Step 6. Finish for the First Time
I started to reframe the piece around that idea and got a finished draft. I recorded it. And then slept on it before I started the audio editing. When I came back to it, I was convinced that it wasn’t right. Maybe it would've been fine, but I didn't like it.
I walked away from it for a few days instead of trying to force it. I didn’t write or edit anything, but I did think about it. A lot.
Step 7. Start Fresh
When I came back to it the next Monday, October 20, I got out the pen and paper again and sketched out a new structure. And then, ignoring the 2,500-word draft I’d completed the previous week, I opened a new tab in the document that I was working in and started writing from scratch.
In this completely new draft, I used a new mental model. I threw out the air sandwich idea. I didn't talk about strategy at all. Instead, I relied on a system archetype called the “drift to low performance.” I extended that mental model to argue that it’s not just that systems often drift into less effective versions of themselves, but that systems—even ones that set out to “disrupt” or “innovate” or create “radical change”—drift back to the status quo.
Even a giant well-funded company like OpenAI on the cutting edge of technological innovation is going to be pulled back by the status quo. Existing systems, incentives, and narratives heavy weights around all of us. You have to be really intentional and cautious about letting it go and not getting pulled back in.
Between October 20 and 22, I rewrote the piece using this framing. I did end up using some lines or ideas from earlier drafts—but most of it was a complete rewrite. Then I recorded it, edited it, and sent it into the world on October 23.
It wasn’t my favorite piece of the year by a long shot. But I was satisfied with it and felt like I’d said something worth saying.
One More Thing
Not everything I write is this labor intensive. Some of what I write feels easy from start to finish. Some is much morelabor intensive that what I’ve detailed here. My point isn’t so much that making sense is hard work, but that it is work. It takes thought and effort and commitment, especially if you want your media or communication to land with people.
But it’s so worth it. Whether you’re trying to communicate something to your team, your clients, your kids, or your city council, we’re all better off when we’re communicating well and making sense of this wild, wild world.
Making Sense is an 8-week workshop series that turns “Wait, what?!” moments into compelling content so you can help your audience make sense of the unexpected.
This interactive seminar combines analysis, research, process, and craft. By the end, you’ll have a draft of an article, episode, video, or social media post (or a detailed outline of a larger work) that makes sense of an experience or question common to your audience.
Making Sense is for media makers of all kinds—writers, illustrators, content creators, speakers, academics, managers, etc.—who aim to turn lived experience and deep analysis into an idea that shifts how others think.
Ready to make sense for your audience? Learn more about the program and enroll.
