I've heard some version of the same advice about five times in the last couple weeks from content coaches, creator newsletters, and other podcasters: in the age of AI, people crave authenticity, so keep your episodes messy, leave in the tangents, don't over-edit. I agree with about 70% of that. It's the other 30% I think we're taking way too far.

In this episode I get into why editing and authenticity aren't actually opposites, the difference between personality-led, entertainment-led, and utility-led podcasts (and why the "keep it raw" advice only really fits two of those three), and the four rules I actually use when I'm editing my own show. Plus the fitness podcast story that's been bugging me for years, from way before AI was even part of this conversation.

If you've ever felt like a podcast made you wait too long for the thing it promised you, this one's for you.

00:00 – Cold open: hearing the same "be more raw" advice five times in two weeks 01:47 – Show intro and the real position: editing isn't the enemy of authenticity 03:39 – Where this take comes from 03:44 – The fitness podcast story: minute 20-something, still no push-up tip 06:14 – The drift problem: interview shows mimicking big-show pacing 07:37 – The framework: personality-led vs. utility-led shows 10:22 – The third category: entertainment-led shows 12:07 – Who's actually listening to a niche show, and when 13:18 – Signifiers of authenticity vs. authenticity itself 16:15 – The constraints argument: why every creative discipline needs them 19:20 – Four practical rules I edit by 21:28 – Wrap: keep the humanity, edit for relevance

If this got you thinking about your own line between raw and just untidy, hit subscribe on Apple or Spotify so you don't miss where this goes next.

And if you'd rather read this one than listen, the written version lands on the blog soon.

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AI search is changing how clients find creative professionals, freelancers, designers, writers, podcast producers, photographers, and other independent creatives online. In this episode, I’m looking at how ChatGPT, Google AI Overviews, Perplexity, and other AI search tools are changing online discovery, what Generative Engine Optimization (GEO) actually means, and what you can do to improve your chances of appearing when a potential client asks AI to recommend someone with your skills. I also dig into why traditional SEO still matters, how AI decides who and what to cite, and why consistent positioning across the web is becoming increasingly important.

I went pretty deep into the research for this one because there are a lot of sweeping claims about AI replacing Google, and the actual picture is more complicated. Google still dominates search, while AI referral traffic is relatively small, but it’s growing very quickly. I also found some interesting evidence that people arriving through AI recommendations may be much more qualified than traditional search visitors. And one of the biggest surprises for me was LinkedIn: individual creators and their content are showing up in AI-generated answers far more often than I expected.

Then I get into what you can actually do about it. I explain why specific positioning tends to work better than vague marketing language, why you should describe what you do consistently across your website, LinkedIn, podcast bio, directories, and other profiles, and why third-party mentions are becoming so valuable. If you publish podcasts or videos, I also explain why transcripts matter for AI discovery. And I’ll give you a simple experiment you can run today: ask ChatGPT or Perplexity the exact question your ideal client would ask when looking for someone like you and see whether you exist in the answer at all.

→ Semrush research on AI referral traffic and AI citations

→ Pew Research on Google AI Overviews and search behavior

→ BrightLocal research on AI-assisted local business discovery

→ Seer Interactive research on AI-referred traffic and conversions

→ Ahrefs research on brand mentions and AI visibility

→ KDD 2024 research on Generative Engine Optimization (GEO)

00:00 Can AI find you? 02:56 Google still dominates, but AI search is growing 03:59 How quickly ChatGPT referral traffic is increasing 05:26 How AI Overviews are changing clicks 07:06 Creative professionals already getting clients through ChatGPT 08:45 Behance, Dribbble, LinkedIn & Upwork 09:47 Why LinkedIn matters for AI discovery 11:10 Why AI-referred visitors may convert better 12:52 What is Generative Engine Optimization (GEO)? 14:41 How AI builds a picture of who you are 15:45 Reddit, LinkedIn & AI citations 17:23 The importance of third-party mentions 18:16 Audit your AI visibility 18:37 Write a specific positioning sentence 19:28 Make your audio and video content readable by AI 19:54 Build third-party mentions 20:44 What all of this means for creative professionals

Subscribe to AI for Creative Professionals for new episodes about AI tools, workflows, creative careers, client work, and what all of these changes actually mean for people who make things for a living.

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Why does having AI handle more of your work leave you feeling more anxious, not less? That's the real question behind this episode on AI burnout and AI anxiety for creative professionals: designers, writers, marketers, anyone whose day is work plus side projects plus a constant queue of content. I break down exactly what the stacking looked like for me: client work, my own side projects, YouTube, newsletters, and Netflix with my partner, all with zero gap in between and why the stacking itself, not any one piece of it, was the actual problem.

So last month I started sitting on my patio most nights around 10pm, thirty minutes, no phone, iced decaf or a zero sugar soda, notebook and pen mostly untouched, my cats usually trying to get in on it too. I talk through how bad I was at just sitting there the first few nights, the voice that kept telling me I should be working instead, and a 2025 Scientific Reports study on why letting your mind wander actually helps creative thinking plus the specific catch on when it works and when it doesn't.

This one's a direct follow-up to the concert episode last week, same underlying idea, opposite setup,

and it connects straight back to my freelance pricing math episode too, on deciding whether to productize, upskill, or step back from production work. If you've been feeling that low hum of overstimulation and couldn't point to why, this is for you.

→ Mind wandering during creative incubation predicts increases in creative performance in a writing task — McDaniel, Habibi & Kaplan, Scientific Reports (July 2025), USC Brain and Creativity Institute

→ Previous episode: the Godsmack concert / collective effervescence episode

→ The overcommitting pattern this episode's guilt voice comes from (episode)

→ Content Overload Is Real — But Attention Spans Aren't Actually Shrinking (episode)

If this one landed, hit follow on Apple Podcasts or Spotify so next week's episode shows up automatically. And if you want the written version of this one plus more episodes like it, the newsletter signup's will be linked soon.

00:00 The small thing that changed everything 01:13 The scene: patio, 10pm, iced decaf, notebook, thirty minutes 02:46 Why "doing nothing" used to feel like wasted time 05:15 What the ritual actually looks like, phone included 07:36 Why it started: work, side projects, content, and Netflix stacked with no gaps 09:40 How AI and algorithms engineer away the gaps between things 10:07 The guilt voice: "I'll just finish this, then I'll chill" 11:29 The research rabbit hole: default mode network and the Scientific Reports study 12:40 The thread connecting this episode to the concert episode 13:25 Bringing it back to your career, side hustles, and the pricing math episode 15:51 The practical takeaway, the patio callback, and next week's tease

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There are experiences AI still can't replace - live music, theater, live sports, and handmade craft all resist AI replication for real psychological reasons, not just sentiment. This episode breaks down exactly why, using concepts like collective effervescence and the effort heuristic to explain what AI can generate versus what it can never actually recreate.

I went to a Godsmack concert last Sunday and for two hours I did not pull my phone out once and somewhere around the third song I felt like I was sixteen again, standing in a crowd at my first real show. I looked around and everyone near me had the exact same look on their face. Turns out there's a reason this hits different and it's not just me getting sentimental in my thirties... there's a real sociological term for it (collective effervescence, if you want to sound smart at a dinner party), plus this thing called the effort heuristic that explains why we value stuff more when we know a human actually sweated over it.

If you're a creative freelancer and your whole thing is "I deliver a fast, polished asset," you're fighting AI on AI's home turf, and that's a losing fight. There's a better move, and I get specific about what it actually looks like. Also: homework. You're picking one hobby and banning AI from it. No arguing.

→ Collective effervescence (Émile Durkheim) — the sociological concept behind why crowds synchronize emotionally at live events → Effort heuristic — the cognitive bias where perceived effort increases perceived value

If you're finding this useful, hit subscribe on Apple Podcasts or Spotify so you don't miss next week's episode.

The written version of this one will be up on the blog soon — link coming, along with the newsletter signup.

00:00: the Godsmack concert and feeling 16 again 02:28: Intro: what this show's about 04:09: Why this hits different: collective effervescence, the effort heuristic, and provenance 07:34: It's not just music: theater, sports, and handmade goods 10:15: What this means for your creative business 14:35: Callback + what's coming next week

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If you're a creative professional - a designer, writer, marketer, videographer, illustrator - using AI tools to work faster and still not seeing your rates move, this episode is probably about you. I'm following up on something I said back in June and didn't fully explain: that I'm thinking about upskilling into something closer to where client revenue actually lives. A month later, I still don't have a clean answer. But I'm thinking through it out loud, because that's what this show does.

I get into why creative professionals who use AI tools to speed up production work tend to hit a pricing ceiling that strategists don't, and it's not a mindset thing, it's structural. I talk about what direct response taught me about proximity to measurable outcomes, what AI actually amplifies in creative work (and what it can't touch), and the question I'm asking myself right now that feels different from "I should probably upskill."

This one doesn't wrap up neatly. If you're a freelance creative doing good work, using the tools, still feeling stuck, it might be worth 17 minutes of your time.

→ AI for Freelancers: The Math Nobody Warned You About episode

New episodes every week - follow on Apple Podcasts or Spotify so you don't miss the follow-up when I actually have something figured out.

The written version of this episode, plus the newsletter, will be added once it's live.

00:00 Following up on June's 2am episode 02:26 Career arc: 2018 to now 04:19 The thing I didn't clock for a long time 05:21 The webinar that reframed everything 07:45 Being three steps from the outcome 09:23 Where AI actually fits in and where it doesn't 12:07 The real risk for creative producers right now 13:04 What I'm doing differently with existing clients 14:38 The bigger move I'm still figuring out 15:26 The question that hits different 16:18 The thing to sit with before you close this app

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If you've ever searched "best freelance business tools" or "simple tech stack for freelancers" at eleven at night instead of doing the actual client work sitting in another tab.... well, same, and this episode's for you.

I break down the four things a service-based creative business actually needs - a website, an onboarding process, one workspace, and a real offer. And where that stack usually balloons into $300-400 a month before you've delivered a single project. Then I walk through my actual freelance tech stack, tool by tool: Netlify for the website, Tally for applications, Notion for the client portal, Slack for communication, Descript for editing, Claude and ChatGPT for drafting, Wise and PayPal for payments. This one's specifically for solo service providers, so you, maybe a VA, maybe a bookkeeper, not course businesses or teams with employees, since those come with different bottlenecks entirely.

If you've got four browser tabs open comparing project management software right now, press pause on that and press play on this instead.

→ Netlify — static website hosting, no plugins or maintenance

→ Tally — free form builder used for client applications

→ Notion — client portal and internal workspace → Slack — private client communication channel → Google Drive — client file storage → Google Calendar & Google Meet — booking and calls → Descript — primary editing, transcripts, captions → Canva — thumbnails and simple design work → Claude — writing partner and repurposing → ChatGPT — brainstorming and image creation → Google eSignature (Google Workspace) — contracts, no separate legal platform → Wise — primary payments → PayPal — backup payments → LastPass — client password collection

If this saved you from opening a fourth pricing tab this week, subscribe on Apple Podcasts or Spotify so next Tuesday's episode just shows up. And if you want the written version of this one plus the full tool-by-tool breakdown, I'll post it here once it's live.

00:00 – Intro 02:20 – Why tool research is actually avoidance 03:01 – Who this episode is (and isn't) for 04:40 – The fantasy tech stack and the $400/month problem 06:44 – The four things every service provider actually needs 07:14 – Thing 1: a simple website 08:24 – Thing 2: onboarding, the most underrated one 09:36 – Thing 3: one workspace instead of six threads 10:03 – Thing 4: structuring the actual offer 12:41 – The two-week rule for adding new tools 13:42 – My real tool stack, tool by tool 16:37 – Final thought: simplicity beats automation

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Is stock photography dead? That's the question that sent me down a rabbit hole this week... after a random Saturday spent bouncing between buying Godsmack tickets, messing with my own website, and generating about forty AI images for my blog. One of them looked exactly like something I would've paid twelve bucks for on a stock site a couple years ago. So I went and checked what's actually happening in the AI stock photography world right now, and it's messier than the headlines suggest.

There's a viral stat going around claiming stock photographer earnings collapsed 98%. I tried to find the source. Couldn't. Turns out it traces back to an unsourced SEO blog post, not real reporting. What IS real: the $3.7 billion Getty Images/Shutterstock merger just fell apart after the UK's competition regulator blocked it, Getty's stock jumped 90% off a new OpenAI licensing deal days later, and individual contributor payouts have genuinely dropped, some by 40%+. I get into where the value moved, and why it's not where you'd think.

This one also goes somewhere I didn't expect: AI-generated fashion models. Zalando, H&M, Mango, and Guess are all using synthetic models now, and the Model Alliance has real concerns about consent and diversity that are worth sitting with. If you're a creative freelancer wondering which parts of your own work are AI-vulnerable versus AI-resistant, this episode is basically a case study for that question - using someone else's industry before it's yours.

→ PetaPixel — coverage of the Getty/OpenAI licensing deal and stock surge

→ PhotoWorkout — source for the $0.78/download average Shutterstock contributor earnings in 2025, down from $1+

→ Brutally Honest Microstock — one contributor's own earnings tracked dropping from ~$1 to ~$0.30/download after Shutterstock's tier reset

→ Model Alliance (Sara Ziff) — advocacy group raising consent and diversity concerns around AI fashion models

→ Model Alliance Press — coverage of the H&M AI "digital twin" models story specifically

→ New York State Fashion Workers Act — official NY Dept. of Labor page on the 2025 law requiring separate consent for AI "digital replicas" of models

0:00 Intro

2:59 Welcome

3:45 Getty & Shutterstock Merger

6:32 Fact-Checking the 98% Collapse Stat

9:20 Where the Value Actually Went

10:28 AI Models & Fashion Industry

12:09 What This Means for Creative Freelancers

14:09 Wrap-Up

If you're finding this useful, hit subscribe on Apple Podcasts or Spotify so you don't miss next week's episode.

If you've got a minute, a review on Apple Podcasts genuinely helps more creative pros find the show. Even just a rating, you'd be doing me a solid.

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If you're a creative freelancer using AI and still not making more money, you're not imagining it — the math in fact doesn't work out the way everyone promises. This episode is the honest, unfiltered version of that problem, starting from a night I couldn't sleep doing that exact math in my head.

I'd been lying awake doing math in my head, realizing I was repeating the exact same overcommitting pattern I swore off in 2025 - saying yes to clients randomly, never actually productizing my own service even though I tell other creative professionals to do it constantly. And the math got worse from there: with everything AI has supposedly changed about how I work, I'm charging roughly the same as I was before any of it.

This one's for my editors, designers, writers, video people, social media managers - anyone whose work sits a step or two away from a client's actual revenue, which makes "just charge more" a lot harder to pull off than the advice makes it sound.

I get into why the work itself slowly gets worse when AI lets you take on more than you can actually hold, what I've started doing differently (including capping my client roster and bundling deliverables instead of taking on more people), and the harder question underneath all of it - whether the real fix is productizing, upskilling into something closer to the money, or stepping away from production work entirely.

I don't wrap this one up with a bow. But if you've had your own version of the 2am loop, I think you'll feel it here.

0:00 Intro

4:50 How the Overcommitting Trap Works

11:21 When the Work Itself Starts to Slip

16:29 Why "Just Charge More" Doesn't Cut It

18:27 What I'm Actually Doing About It

25:54 The Question to Sit With

26:17 Your Way Out

If this one hit home, hit subscribe on Apple Podcasts or Spotify so the next episode lands in your feed automatically.

The written version of this plus a couple of things that didn't make it into the recording — is up on my newsletter and Substack.

Come find me on Instagram or Substack.

If you've got a minute, a review on Apple Podcasts helps other creative pros find the show. Even just a rating helps more than you'd think.

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