Natalia Quintero is the head of consulting at Every.
'AI & I' with Every's Katie Parrott
The transcript of AI & I with Every staff writer Katie Parrott, hosted by Natalia Quintero, is below. Watch on X or YouTube, or listen on Spotify or Apple Podcasts.
Hey, it’s Dan Shipper, and this week I’m excited to share a very special episode of AI & I . In this episode, we’re previewing the release of an experimental new plugin called Compound Writing, which helps you write with AI the way that we do internally. It’s inspired by Kieran Klaassen’s Compound Engineering, and it’s built by one of our staff writers, Katie Parrott.
To help talk about this plugin and why Katie made it and how she uses it, Natalia Quintero is the host of this episode. She’s our head of AI consulting, and she’s been on the podcast a few times, and she’s just an incredible interviewer. So I’m really excited for you to hear Katie and Natalia chat.
Today we’re talking to Katie Parrott, staff writer at Every. Katie, if you’ve been following Every for a while now, she’ll be very familiar to you. She’s one of our all-star writers, and we’re so excited to learn more about her writing process and her new plugin today.
So good. I am so excited for this conversation. I am revealing myself as a Katie fangirl on the podcast.
Okay, so Katie, almost exactly two years ago, you wrote one of your most popular pieces for Every, and it was about how you had just been laid off. And also maybe we’re in the middle of a mental health crisis, which you’ve written publicly about. And you decided to turn to ChatGPT as a career coach. But at the time you were also an AI skeptic, which might be crazy to think about now given some of the work that you’re doing. Can you take us back to that period? What was going on in your career, and in that moment in time that led you to turn to ChatGPT in the first place?
Yeah, so I had just been let go from a crypto firm, where I was working as an editor and ghostwriter for the team. It was traumatizing at the time, but in hindsight it was like the best thing that ever happened to me, because it led me back to Every.
I was feeling really lost. As you mentioned, I had tried crypto, I had tried in-house, I had tried out-of-house, I had tried all these different things, and I felt like I was at the end of what I could do on my own. I really needed an outside perspective, but because I was working on a budget with no clear visibility into how long I would be unemployed, hiring a real career coach wasn’t really an option for me.
So I had some exposure to ChatGPT at that time. I had actually used it to produce briefs at a previous job as a content marketing manager. We had an agency, and I realized I was hitting a wall of depression at that job and could not bring myself to put words on a page. But I found that if I used ChatGPT to generate some of the repetitive stuff, it became this assistive tool that I used as a tool for thought — a phrase I’d also seen Dan use around the same time, because I was following Every at the time.
Yeah, it’s such a cool post that you wrote, and you always have such great zingers in your writing that are just so delightful to read. I hope when we’re sharing this on video we can pull up some of the screenshots of what your ChatGPT prompts looked like, because it feels vintage to be looking at chats from two and a half years ago.
But in that post you have this really great quote. It’s a little lengthy, but I’m going to try to read it because I have a question about it. You say: “One of my favorite things about writing is that I never know what I think until I write it down. But once I write it down, it becomes obvious. Ultimately, what’s prompting ChatGPT is a form of very specific strategic writing. Do I think my experiment with ChatGPT added clarity in my thinking? Yes, it has. But as with so many of these tools, the real work is still mine. Clarity, it turns out, doesn’t arrive gift-wrapped from a digital assistant or even a human coach. It’s something I had to dig out for myself, question by question and prompt by prompt. True clarity, direction, and answers come from the process of engaging with the prompts and doing the hard work yourself. AI can help guide the way, but the journey is yours to take.”
Just so beautiful, so cool. I think one of the things that really resonates with me about your writing is that it feels so reflective of my own experience using AI, where I’m attracted to the possibility of maybe an easy answer, an easy solve. But actually what I constantly find myself doing is learning something that was always there inside of me, but I had to put some work in to actually get it out.
Can you tell me a little bit more about what using AI in this very early, very practical experience taught you about using AI?
The first thing it taught me is that I can use AI to make change in my life, which is something I’ve continued to carry through over the last couple of years. I really judge the technology by the impact it’s had practically for me.
I remember, when I got the invitation from Kate to write what ultimately became Working Overtime, my column, I was talking to ChatGPT about whether it was the right step for me to take, because I was kind of on the fence — it would have been freelancing at the time, versus looking for a full-time opportunity. And ChatGPT nudged me in the direction of, well, why not try it in the meantime? And I did that, and now I’m here.
Throughout my experience with AI, that’s really been the thing: it’s given me both the framework for thinking, and obviously it’s become the thing I think about, but it’s really just about the fruits of the labor, so to speak, and seeing what AI is able to give back to me.
So it sounds like one of the early takeaways you had in leveraging AI was that you could really get it to be a valuable tool for you. That reminds me of another post you wrote that was really popular with the Every audience — I believe it’s titled “AI Turned Me Into a Content Agency of One.” Early in this post, you talk about how, as a freelancer in early 2025, you realized you had potentially overcommitted yourself with the number of freelance projects you’d agreed to deliver. You list what you committed to delivering in a two-week period: eight blog posts, three ebooks, 24 LinkedIn posts — we’re not even halfway through — 24 X posts, 16 Instagram posts. There is just no way you could write this amount of content in a month. How did you learn to use AI to generate this amount of content, and at the caliber you deliver?
I think around this time was when I was really discovering — I wouldn’t have used this language because it hadn’t really become a thing yet — context engineering. What I realized was, if I gave the model a really good foundation in terms of the brand messaging, product specifics, and audience specifics of the companies I was working for, I could shape the AI outputs toward the direction I wanted. So it was really a lot of foundational work that, once it was set, I could just iterate through.
It helped that a lot of the things were content repurposing, which is one of the first things people were really excited about — one of the first products Every put out was Spiral, which was all about content repurposing, because that’s something Every was doing a lot of. You have a post, you want to turn it into a LinkedIn post, a Twitter post, a blog post.
So it was like, okay, I’ll write through all of the surrounding information the AI needs to do a good job. The more I put in that work up front, the easier the process got farther down the line. That’s something I found with my AI experience overall: at first it feels really effortful, and you’re spending a lot of time setting the scene — getting everything lined up in terms of your tools, your integrations, your context documents. But once you have that environment set up, you can just run, and run fast. That’s what let me do it when I overcommitted myself that time — which I did again about six months later. I think this might be a common characteristic of everyone at Every.
Can we talk a little bit more about what was in those files — what the context and setup looked like that let you go fast? I remember some of the context files you shared with us around that time, but I’m curious. Were they folders you were sharing? Were they projects on Claude? Walk me through what some of those things looked like.
They weren’t projects, because projects didn’t exist yet. When projects launched, I thought back to that period and was like, I really wish this had existed when I was doing this, because I had to do a lot of manual copy-pasting. I would have my persistent documents in a Google Doc, and I would copy and paste into the context window so the model would have access to that information.
It really came from my experience in the content marketing world building style guides. Every brand worth its salt has a source of truth where they document: who is our audience, what are their pain points, how does our product map to those pain points, what is our competition, and what are our differentiators. These are units of work I was used to doing as a content manager. I just started with what I was familiar with and gave that information to the model. It did a good job, and I was like, okay, this seems to be working.
Then projects came along, and suddenly I didn’t have to copy-paste anymore, because I could use the project documents and the custom instructions to set a project up. I had a project for every freelance client, a project for every column I worked on, because I was starting to spread out in terms of what I was doing at Every at that time. But it all comes down to basic rules of writing — knowing who your audience is, what your differentiated thing is to say — and just feeding the AI all of that foundational stuff so that it feels true, so it has rails to run on. I always think of it as creating guardrails, a fenced-in place for the model to play, so you don’t have to worry so much about getting something completely wrong, because you’re pushing it in the right direction.
Right, you’ve given it a playground. I know this is something Mike Taylor on our team cares a lot about — having really clean context windows and being very selective about what playground you’re giving the model.
Knowing what you know now, as a writer, what are the things you think have made your projects so successful? Is it having a really strong point of view on what good writing is, on what good content marketing is? What are the things that are so important to have a strong perspective on?
I think it’s less about the writing at first than it is about the other kinds of context — the data you’re giving it, the frameworks for audience personas and who they should be talking to. You need all of that in place before you can even get to stuff like “use these words, avoid these words,” “prefer this level of reading difficulty,” “strike this tone.” Before you even get to the point of messing with that kind of stuff, you need to have those foundational elements set up. We’ll be wrestling with diction and syntax for the rest of forever.
And when you’re referring to the data, what is the data you need to put in there?
That’s the specifics of the piece. Something I feel really strongly about, as our role as humans in this wonderful world of AI and AI writing specifically, is that there’s a last-mile problem in AI and writing: AI has that knowledge cutoff, right? It’s always working with data that’s several months out of date. Our job as humans is to close that last mile and provide the real-world experiences AI can’t get, because they come after the knowledge cutoff, and because it’s happening out there in the real, physical world, and AI is not in the physical world yet.
So when I say research, I’m really talking about the unique insight — whether that’s a study your company has produced, or third-party research you’re pulling in, which is something I love to do in my writing for Working Overtime. Those are all the constitutive elements that go into the writing, and the model can then work from that. But the inputs are really what makes the writing unique.
A lot of times when people are writing with AI, they’ll just go to it and say, “write a blog post about style guides,” and they don’t give it anything to go on — they’re just asking the model to write from what it already knows. But what the model already knows is commoditized information. That’s not useful or interesting. So the data is the unique insight, the data point the model doesn’t have access to yet, the personal experience — all of those things are what’s ultimately going to make the writing unique.
It all sounds like the documents you’d save for what might be a project today, or maybe a Codex setup — all the things that can be codified as good best practices. But what you bring into every piece is like the quality of the ingredients. So it sounds like what you’re bringing to the piece is the freshness, the quality, the unique elements you want to highlight and bring out — that only you can really bring.
I love that analogy — that’s a really good one. That’s pretty much exactly it. The model is the kitchen — the structure, the outline, is like chopping, and the composition is like boiling. But you need the individual ingredients to be fresh and good to produce good work.
This is actually something you referenced very early on in a piece from 2025. You have this really beautiful quote — I’m sorry to read you your own great quotes back to you, it’s horrible — you write: “Two-odd years into my AI journey, I have to admit AI hasn’t just helped me produce content faster. It has fundamentally changed the scale of what I can do. The limits I used to bump up against — time, energy, capacity — are way lower.”
It sounds like that’s the recipe, right? You’d always be using the same recipe, but now you don’t have to worry so much about the recipe — it’s codified, and now you can just come to the table with what’s uniquely in your brain. You also say in the post: “It’s become trite to say that AI frees you to focus on the human elements that truly matter, but AI has freed me to focus on the human elements that truly matter.”
It’s magic seeing it from the outside, you know? I have no idea how you do it, and it’s magical every time you put another piece together.
It’s magical to me too. Working with AI kind of made me fall in love with writing again, because for a long time writing felt like such a slog. It was so effortful — I was spending so much energy and mental capacity just trying to assemble sentences that I wasn’t really paying attention to what the sentences as a whole said. I was just like, this is done, good enough, get it off my plate. Now, with AI, I have the energy left over to spend more time wrestling with the harder, bigger-picture questions. It’s made writing a lot more fun, because it’s brought back a feeling of exploration and discovery, both with the tool and with my own brain — what I think, and how I bring that to life.
I want to turn back for a moment. There are two things I admire so much in the way you use AI. One is obviously the way you use it for writing, but the other is the way you use it as a harness for doing your best work. You have this really beautiful piece you wrote about a year ago, in mid-2025, called “AI Solved the Problem That I Couldn’t Explain to Managers.” Can you tell us a little bit about this piece? Do you remember what you talked about?
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This is the piece where I talk about my mental health and my crippling anxiety around email.
This is one of the most personal pieces I’ve written, and one of my favorites, because it’s about AI viewed through a different lens than we’re used to thinking about it. We think about AI as a productive technology — we value it for its ability to produce output, to get things out. What I found in my personal experience is that AI is just as powerful as a supportive technology.
I have bipolar disorder. I experience spikes of high energy, and honestly, I spend a lot more time in really low periods of depression. What I found is that AI reduces friction in my life in a way that makes it easier for me to move through my day-to-day life. That’s actually become even more true now, with agents being able to handle what our COO, Brandon, calls “computer errands.” I put off making a primary care physician appointment for three years, and then I realized I could simply tell Codex to go find primary care physicians near me who take my insurance and are accepting new patients. It went off and found me someone, and I booked an appointment. I would never have done that — I would have kept procrastinating on it infinitely because of the way my brain works, and AI was able to help me over that hump. It’s done that over and over again.
Using Cora to make my inbox more manageable, so I’m not confronting a wall of emails but just the really important ones that need my human response — that’s completely changed my relationship to my inbox, because I don’t have to go digging around, looking for the bomb hiding among the millions of subscription notices and things like that. The things that need a human response come to me. Now I have an automation set up through Codex that tells me what’s in my inbox that I need to respond to, and my inbox anxiety has been completely resolved.
I’ve seen a lot of other ways AI supports me and allows me to work better — not just using it for the output, but for everything that surrounds the output.
Right — it’s not just the medical appointments, it’s the bills, the emails, the tasks you’ll never really get around to doing around the house or whatever it might be. It does feel like, with AI, I have a little more firepower to get to some of those things. You’ll love this, Katie — for the first time in my life, I’m filing my insurance reimbursements through Codex instead of doing it by hand. It’s exciting to have a tool that can really work in my favor.
In this piece, you also say: “I’ve been working at Every for one year now, and that might not sound remarkable, but it feels like a milestone. For me, the proof of AI’s value is the fact that I’m still here, doing work I’m proud of.” That’s the greatest measure of success — getting to do more of the work you’re excited to wake up and do every day.
So we started out with you going to ChatGPT over two years ago and asking it to be your career coach, and it’s enabled this incredible amount of work you’re doing now. Now it looks a little more like a Codex project, if I understand correctly. Can you tell us a little more about how that’s evolved, and what it looks like today?
This is about the career coach — what the equivalent of your career coach looks like today.
Oh my gosh, my career coach has evolved so much. It’s now a project inside Codex, and it has so much more information than the first version. It has a dossier on me and my role, and context around Every and our super-top-secret brand positioning that I got from our head of marketing, Douglas. What I’m able to do with that is: here’s the context on me and my role, here’s the context on Every, how do I put those two things together, and what should I prioritize to have the biggest impact I can?
Now that I’m in a job and not looking for one, it helps me orient myself, prioritize, and it does project management for me. Increasingly, all of this is happening just with voice, with Monologue. I’ll monologue a ton all day, every day, and just talk to my career coach about — I’ve got four different priorities, what should I do in what order? It kind of operates as a chief of staff that points me in a direction and says, this is the highest-impact thing you can do first, this is something you can put off until later. And it maintains a Kanban board for me. I’ve never been a person who can maintain a Kanban board, but now I don’t even have to touch it — it just lives in this career-coach management project, and I just ask, what’s the due date on this deliverable, and it tells me.
Can you tell us a little bit more about how that’s set up? That sounds incredible.
You kind of forget over time, as it starts working, that you take for granted it’s working and don’t think about what’s inside it so much anymore. Let me find career coach mode...
So in two years — which is a lot of time in AI time — you went from a simple prompt on ChatGPT, “how can you help me as a career coach,” to having a fully autonomous Codex setup that maintains your to-do list, your OKRs, keeps you on track with a Kanban board, and at this point Codex is maintaining it for you.
I think one of the things you’re uniquely great at is using AI to power your career harness, and also your ability to write really great pieces. Going back to the writing component — we talked a little about how you’ve gotten AI to hold the recipe for you, how you think about good writing, and the elements you bring to each writing session so you can do your best work. By the time this podcast airs, we will have published your Compound Writing plugin. Can you tell us a little bit about what compounding is as a concept, and then about the writing plugin?
Yeah, so compounding is the idea that every piece of feedback you give to AI should feed back into the system to improve the next output. Folks who follow Every will be familiar with this from Kieran Klaassen’s Compound Engineering plugin. He was really the one to pioneer this idea — that you should only have to give a piece of feedback once, but if you codify it the right way, it will be there forever, and the next time you’re in that same situation, the AI is going to make a better decision.
The Compound Writing plugin — I literally just forked it. “Forked” is a word I know now because I wouldn’t have known it if I weren’t working with AI, but I pulled the Compound Engineering plugin down and talked to Claude about it, and said I wanted to adapt it for writing. Because in certain ways, writing is very similar to code. Compound Engineering has brainstorming, ideating, planning, working, and reviewing. Very similarly, in writing you have brainstorming, outlining, drafting, reviewing — it’s a similar flow, but there are differences. Obviously, in writing you’re not looking at things like coding conventions, you’re looking for things like structure, voice, evidence. So it’s a different container, but it just made sense to me.
I talked to Claude and said, I want these steps in the process, I want an outline to look like this, I want a draft done this way, and I want two different kinds of review — a substantive edit that’s about the big-picture structure and argument, and a line edit that looks at the individual writing, and then a final pass that looks at the final details you want before something’s publication-ready. I was able to pull that together — like all of my best AI ideas, I ripped off from someone else on the Every team. It was very much Compound Engineering plus Dan’s agent-native architecture guide, combined to create Compound Writing. That’s what I use now for every piece I write. I’m no longer in a chat window, no longer in a project on Claude.ai or ChatGPT.com — I’m in the Claude desktop app or the ChatGPT desktop app, working with this system that has the recipe for how I want the drafting process to go, plus the context files — many of the same ones that used to live in the project, like a style guide, example pieces. Then I bring the fresh information into that ecosystem, and a piece comes out of it, one way or another.
I’m so excited to use it when it comes available. I hope to be an alpha tester when you’re ready to share it.
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