AI DTC WTF

Is AI Making You a Worse Marketer? | Ben Feys, PrettyBoy

Foxwell Digital — Thu, 15 Oct 2026 03:00:00 +0000

Is AI making you a worse marketer?

AI makes you a worse marketer when you use it to skip work you never learned to do, and a better one when you use it to speed up work you already understand. Ben Feys runs PrettyBoy with one co-founder and holds every AI build to three tests: the result has to be measurable, it has to beat the alternative, and it has to save money. He automates research, planning and briefing on workflows he knows end to end, keeps people on the creative judgment, and tracks AI-made ads separately from human-made ads so the performance question gets settled by data.

In this episode, Andrew Foxwell and Will Sartorius ask Ben Feys, co-founder of PrettyBoy, how a two-person DTC brand uses AI to get more done without losing the skills that make the work good. Ben explains the three tests every AI build has to pass, why he tracks AI-made ads separately from human-made ads, and why he thinks human-written content could be a small brand's moat.

PrettyBoy is a men's skincare brand run by Ben and his co-founder Kevin Niehoff. Ben automated the brand's email workflow end to end with Claude, built a company brain on top of their ad, retention and creative data, and has strong opinions about where that stops paying off.

We discuss:

The three tests a two-person team uses to decide whether an AI build is worth it
Automating an email workflow with Claude, from performance analysis to briefs loaded into ClickUp
Why vibe coding your own version of a SaaS tool is misguided for most operators
How automating creative entirely makes you settle for "nice enough" ads
Tracking AI-workflow ads separately from human-workflow ads to see which actually perform
What a company brain is good for, and the two kinds of people who benefit most
Why AI works best for people who already know how to do the job
Why hiring for "Claude native" backfired, and what to hire for instead
How to use AI as a creative strategy teacher instead of a shortcut
Why going all in on human-made content could be a small brand's moat

Show site: https://www.ai-dtc-wtf.com/
Connect the Foxwell MCP to Claude or ChatGPT: https://www.foxwelldigital.com/mcp

Guest: Ben Feys, Co-Founder, PrettyBoy
PrettyBoy: https://www.yoprettyboy.com/
Ben on X: https://x.com/fenbeys
Ben on LinkedIn: https://www.linkedin.com/in/benjamin-feys-23112950/

This Episode is sponsored by Motion's very own Runneth. Runneth is the AI Tool that is quickly becoming the go to decision maker brands turn to when it comes to creative decisions within their ad accounts. From Creative strategist to hook inspirations and creative briefs, runneth can do it all. See the case studies and try runneth yourself https://runneth.com/

AI DTC WTF is the show for brand owners, in-house advertisers and agency operators who use AI every day and want tactical workflows they can implement now. Published by Foxwell Digital: https://www.foxwelldigital.com/

To connect with Andrew Foxwell reach him here Andrew@FoxwellDigital.com
To connect with Will Sartorius DM him here https://x.com/will_sartorius
To connect with Thomas Moen DM him here https://x.com/thomasmoen
To learn more about Foxwell Founders and conversations like this one, go here: https://www.foxwellfounders.com
Learn more about Foxwell Digital and join our newsletter: https://www.foxwelldigital.com/email

Chapters

00:00 Is AI making you a worse marketer?
02:28 Automating an email workflow with Claude, from analysis to ClickUp briefs
05:16 Why vibe coding your own SaaS stack rarely pays off
07:00 Does automating ad creative make your ads worse?
08:55 What a company brain is good for, and who it helps most
15:29 Why AI works best when you already know how to do the job
19:54 Why hiring "Claude native" strategists backfired
23:25 What to look for in a creative strategist now
29:29 What running a DTC brand looks like a year from now
32:54 Why human-made content could be a small brand's moat

How to Hire Creative Strategists When AI Writes Every Sample | Jess Bachman, FireTeam

Foxwell Digital — Wed, 30 Sep 2026 16:46:00 +0000

How do you hire creative strategists and copywriters when AI writes every work sample?

Stop judging creative strategists on work samples, because you can no longer tell what the candidate wrote and what AI wrote. Make them do the actual job instead: FireTeam's AI interviewer hands candidates a deliberately flawed brief, asks them to find and fix the problems, pushes on why each fix is right, and flags pasted answers. Past that screen, the strongest signal is proof that someone builds and tests with AI while staying skeptical of its output, such as a steady record of GitHub commits. In this episode, Andrew Foxwell and Will Sartorius talk with Jess Bachman, co-founder of FireTeam, about how to hire creative strategists and copywriters when AI writes nearly every work sample. You'll learn how Jess's AI interviewer tests how candidates think, how FireTeam's AI brief writer outperforms a strong human copywriter, and why he would judge a creative strategist by their GitHub commits. Jess runs FireTeam, a performance creative agency that gets paid when ads win. He deployed the AI interviewer to hire a copy engineer and has iterated on it since, and every FireTeam brief now runs through the agency's AI brief writer. We discuss:

Why work samples stopped being a useful way to hire creative talent
How an AI interviewer uses a deliberately broken brief to show how a candidate thinks
Paste detection, dictation false positives, and whether AI screeners turn off good candidates
How FireTeam proved its AI brief writer beats a human copywriter, using its own win data
Why AI is still terrible at coming up with ad ideas, and what the team does instead
Why client learnings, not the prompt, drive 75% of the results
Why Jess keeps performance analysis entirely human
Why the creative volume game is not coming from Andromeda
Why AI raises the floor to a C but cannot turn someone into a builder
The hiring signal Jess trusts most for AI-era creative strategists

Get the newsletter: https://www.foxwelldigital.com/email Listen to the full podcast: Apply to Foxwell Founders: https://www.foxwelldigital.com/apply Guest: Jess Bachman, Co-Founder, FireTeam FireTeam: https://fireteam.is Jess on X: https://x.com/HireFireTeam Jess on LinkedIn: https://www.linkedin.com/in/jessbachman/ To connect with Andrew Foxwell reach him here Andrew@FoxwellDigital.com To connect with Will Sartorious DM him here https://x.com/will_sartorius To connect with Thomas Moen DM him here https://x.com/thomasmoen To learn more about Foxwell Founders and conversations like this one, go here: www.foxwellfounders.com Learn more about Foxwell Digital and join our newsletter: https://www.foxwelldigital.com/email This Episode is sponsored by Motion's very own Runneth. Runneth is the AI Tool that is quickly becoming the go to decision maker brands turn to when it comes to creative decisions within their ad accounts. From Creative stratigest to hook insporations and creative briefs, runneth can do it all. See the case studies and try runneth yourself https://runneth.com/ Chapters 00:00 How to hire creative strategists when AI writes every sample 02:17 Inside FireTeam's AI interviewer and its deliberately broken brief 04:16 Paste detection, and whether AI screeners scare off good candidates 07:21 How an AI brief writer beat a human copywriter 10:44 From a brainstorm gist to a finished brief in 30 minutes 16:33 Why your data, not your prompt, makes AI copy win 21:29 Does AI only help people who could already write? 22:24 Why the creative volume game was never real 27:50 Can AI turn an average employee into a 100x employee? 31:52 Why GitHub commits are the new creative strategist portfolio

How Go Brewing Built Their Entire Business Operating System With Claude Code | Joe Chura | EP 14

Foxwell Digital — Wed, 16 Sep 2026 15:50:00 +0000

How do you build a business operating system with Claude Code? You build it one component at a time and connect them, rather than building isolated dashboards. Start with the smallest painful process you already pay software for, rebuild it so it writes to your own database, then make the next tool read from that same data. Joe Chura rebuilt his brewery's sensory testing app in a single evening in Claude Code, tied it to batch numbers, then layered on customer support, wholesale onboarding, creative production and retail campaigns until every system in the company shared one set of records. The test for each piece is whether it increases revenue or reduces cost, not whether it is impressive.

In this episode, Andrew Foxwell and Will Sartorius talk to Joe Chura about how to build a business operating system with Claude Code instead of buying and stitching together software. Joe rebuilt his brewery's production, support, wholesale, creative and retail systems himself in about 90 days, and explains how the pieces connect, which builds paid off fastest, and why isolated dashboards are the mistake most operators are making right now. Joe founded a digital marketing agency in 2011, grew a software company from $0 to $40 million in revenue in five years, sold it to Cars.com, and ran a 1,000-person organization with 100 developers. He now runs Go Brewing, a non-alcoholic brewery he says was the fastest growing in the country last year, with three salespeople. We discuss: - Why Joe rebuilt a cheap sensory testing app instead of renewing it, and what that unlocked - How to connect internal tools so batch data, customer complaints and cost anomalies all read from one source - Turning customers into a sales force with an ambassador app that pays out on validated leads - Why the rate-of-sale math on non-alcoholic beer makes traditional field reps uneconomical - A full screen-share walkthrough of Brewery OS, from nightly bug sweeps to a tank planner that saves a week of work - The three highest-ROI things to build with Claude Code, starting with your Shopify theme - How connecting GitHub to a Shopify theme took Go Brewing's conversion rate from under 5% to 10% in a weekend - Using Claude Design to build a design system, then handing it to Claude Code as a prompt - Why reading Microsoft Clarity every day is the cheapest optimization loop in ecommerce - The mindset shift that is harder than the technology: getting a team to stop asking for reports

Never Miss and Episode: https://www.ai-dtc-wtf.com/aidtcwtf-newsletter To connect with Joe Chura, Founder and CEO, Go Brewing Go Brewing: https://gobrewing.com/ Joe on LinkedIn: https://www.linkedin.com/in/joechura/ To connect with Andrew Foxwell reach him here Andrew@FoxwellDigital.com To connect with Will Sartorious DM him here https://x.com/will_sartorius To connect with Thomas Moen DM him here https://x.com/thomasmoen To learn more about Foxwell Founders and conversations like this one, go here: www.foxwellfounders.com Learn more about Foxwell Digital and join our newsletter: https://www.foxwelldigital.com/email This Episode is sponsored by Motion's very own Runneth. Runneth is the AI Tool that is quickly becoming the go to decision maker brands turn to when it comes to creative decisions within their ad accounts. From Creative stratigest to hook insporations and creative briefs, runneth can do it all. See the case studies and try runneth yourself https://runneth.com/ AI DTC WTF is the show for brand owners, in-house advertisers and agency operators who use AI every day and want tactical workflows they can implement now. Published by Foxwell Digital: https://www.foxwelldigital.com/ Chapters 04:19 What was the bottleneck before Claude Code? 06:55 Rebuilding the first internal app in Claude Code in one evening 09:50 Turning customers into an extension of the sales force 14:39 Sponsor: Runneth from Motion 15:50 How to decide what to build next, and in what order 19:02 Why team mindset is the real bottleneck, not the technology 24:21 Screen share: a full tour of Brewery OS 35:53 Live demo: building a retail campaign end to end 39:40 The three highest-ROI things to build with Claude Code

Fable 5.1: What Actually Changed and What to Use It For | EP 13

Foxwell Digital — Thu, 10 Sep 2026 04:20:00 +0000

Is Fable 5.1 actually better, and what should a marketer use it for? Fable 5.1 is a net improvement on Fable 5 for marketers, mainly because it is more concise and burns fewer tokens, which makes it cheaper to run for the same work. Its highest-value use is not writing copy. It is auditing the skills, agents, and markdown files you already built, finding the redundancies that were making them skip steps, and then running the cleaned-up prompts on a cheaper, faster model. Video work and translation are dramatically better than they were a few months ago. Image generation is not, and dedicated tools still win there.

In this episode, Andrew Foxwell, Thomas Moen, and Will Sartorius break down what actually changed in Fable 5.1 and what it is genuinely good for. You'll learn why it is cheaper to run than Fable 5, why the best use is auditing the skills you already built rather than writing new copy, how to route tasks across different models instead of paying for the expensive one every time, and why video translation went from unusable to production ready.

We discuss:

- What changed between Fable 5 and Fable 5.1, and why it costs less to run - Why the highest-value use is auditing your existing skills, agents, and markdown files - The prompt audit that found the redundancies making skills skip steps - Why you should run cleaned-up prompts on a cheaper model instead of the flagship - How to route specific tasks to specific models: planning, coding, research, execution - Why less instruction now produces better output, and the Meta ads parallel that explains it - The claim that Fable 5.1 copy carries a detectable watermark, and what that means for blogs and newsletters - Why the writing finally stopped reaching for bold headers and three-item lists - The rise of the AI-forward individual contributor, and how to become one - Why one agency won't let a creative strategist touch an AI tool until they can do it analog - Why Thomas's agency stopped hiring junior people entirely - Localizing an entire instructional video library by dropping MP4 files in - Why image generation still belongs in HiggsField and not here - Tagging a folder of B-roll with Gemini Flash and cutting mashups in Claude Code To connect with Andrew Foxwell reach him here Andrew@FoxwellDigital.com To connect with Will Sartorious DM him here https://x.com/will_sartorius To connect with Thomas Moen DM him here https://x.com/thomasmoen To learn more about Foxwell Founders and conversations like this one, go here: www.foxwellfounders.com Learn more about Foxwell Digital: https://www.foxwelldigital.com All episodes: https://www.ai-dtc-wtf.com Join The AI DTC WTF Newsletter: https://www.ai-dtc-wtf.com/aidtcwtf-newsletter Join the Foxwell Digital email list: https://www.foxwelldigital.com/email

This episode is brought to you by Runneth by Motion: https://runneth.com/

AI DTC WTF is the podcast for people who work in DTC, use AI, and want to know what is actually working right now. Every week: tactical tips, strategies, and ideas you can implement in your AI workflows to make your brand or agency more money.

Chapters

00:53 Why Fable 5 was too greedy with tokens 01:30 Fable 5.1 is more concise and cheaper to run 01:45 Which model to use for planning versus doing the work 02:12 Why Anthropic keeps botching the marketing 02:26 The limits announcement that said 50% and meant 17% 02:42 Why skills kept skipping steps 03:23 The prompt audit that found the redundancies 03:53 You don't need the expensive model for everything 04:42 How to stay agnostic and route tasks across platforms 05:20 What Grok is genuinely faster at 06:20 Using Grok for small coding and research tasks 06:43 How to actually tell a model which model to use 07:14 Why stripping down your markdown files gets better output 07:31 The Meta ads parallel: less micromanaging, better results 08:19 Auditing a brief flow that was writing copy before finding personas 09:01 The watermark on Fable 5.1 copy, and what it means for blog posts 09:19 Why the writing finally stopped sounding like AI 10:53 The rise of the AI-forward individual contributor 11:47 Why creative strategists here can't touch the tools yet 12:18 AI as a compass, not a destination 12:39 How to learn creative strategy the old fashioned way 13:41 Amplifying good people versus replacing them 14:54 Why this agency stopped hiring junior people 15:49 Why Europe is further behind than the feed makes it look 16:56 Video and image generation on Fable 5.1 17:41 Localizing a whole Norwegian video library in a week 18:15 Why better reasoning makes project orchestration better 18:56 Dropping MP4 files in and getting a finished English version 20:03 Why images still belong in HiggsField 20:51 Tagging B-roll with Gemini Flash and cutting mashups in Claude Code

The 4 Skills That Turn a Media Buyer Into an AI Growth Strategist | Rooster Sanchez

Foxwell Digital — Thu, 03 Sep 2026 10:00:00 +0000

What is an AI growth strategist, and what does a media buyer or account lead have to learn to become one? An AI growth strategist is the person accountable for a brand's entire funnel and its financials, not just the creative, doing that job with AI wired into every step. Becoming one takes four skills in order: context engineering, so the model knows your business; skills, so you can replicate yourself instead of prompting from scratch; connectors, so the model queries live data instead of a stale onboarding doc; and being the person who pushes AI through the team's actual workflow. Get those four right and the analysis that used to need a data scientist and a two-day lockout becomes a morning Slack digest. In this episode, Andrew Foxwell and Thomas Moen talk with Rooster Sanchez about what the role of an AI growth strategist actually is and the four skills it takes to become one. Rooster explains why context engineering comes before tooling, which connectors are non-negotiable for anyone running accounts, how his team replaced a two-day strategy lockout with a morning Slack digest, and why eliminating a process beats automating it almost every time. We discuss:

What an AI growth strategist owns that a media buyer or account manager doesn't
The four foundational skills: context, skills, connectors, and being the point person
Why you no longer need a data scientist for cohort, LTV, and product-level profit analysis
The folder structure that makes Claude find things faster across a whole client roster
Why migrating meeting notes into the model was the single biggest unlock for client comms
Building a card per client so AI knows how each one wants to be reported to
The must-have connectors for a growth role, and where Google Meridian fits for larger accounts
The alert stack: creative fatigue, audience saturation, CPM spikes, net new reach drops
Why the number one reason clients churn has nothing to do with performance
Elimination before automation, and how to run your SOPs through that filter
Logging every scheduled task so AI spots trends across your whole client base
The prompt that stops AI from being sycophantic, and what it reveals
Why every landing page now looks the same, and why that makes brand a moat

Resources mentioned:

llm-wiki, Andrej Karpathy's pattern for organizing AI folders: https://gist.github.com/karpathy/442a6bf555914893e9891c11519de94f
The anti-sycophancy system prompt, attributed to Marc Andreessen: https://substack.com/@linas/note/c-257971365
Google Meridian, open-source marketing mix modeling: https://developers.google.com/meridian

This episode is brought to you by Runneth from Motion: https://runneth.com

Join the AI DTC WTF email list: https://www.ai-dtc-wtf.com/aidtcwtf-newsletter To connect with Rooster Sanchez LinkedIn: https://www.linkedin.com/in/luisfersanchez/ To connect with Andrew Foxwell reach him here Andrew@FoxwellDigital.com To connect with Will Sartorious DM him here https://x.com/will_sartorius To Connect with Thomas Moen DM him here https://x.com/thomasmoen To learn more about Foxwell Founders and conversations like this one, go here: www.foxwellfounders.com Learn more about Foxwell Digital: https://www.foxwelldigital.com All episodes: https://www.ai-dtc-wtf.com

Apply to Foxwell Founders: https://www.foxwelldigital.com/apply

Learn more: https://www.foxwelldigital.com/

Chapters

00:00 What an AI growth strategist actually is 01:05 Why AI amplified agency roles instead of replacing them 02:33 The role that owns the whole funnel, not just the creative 03:55 Why you no longer need a data scientist for cohort and LTV analysis 05:18 The case for 10x growth strategists 06:00 The four foundational skills: context, skills, connectors, point person 07:57 Sponsor: Runneth by Motion 09:11 Organizing your Claude folders with Karpathy's llm-wiki 10:08 Why moving meeting notes into AI was the biggest client comms unlock 11:05 Building a card per client so AI knows how each one wants to be reported to 12:04 How Claude indexes your work so context never goes stale 13:14 The must-have connectors for a growth role 14:07 Using Google Meridian to build your own geo holdout tests 15:19 How AI juries and alert stacks find problems before they become fires 17:29 Cutting three hours a day out of account management 17:42 How to avoid using AI to do 10x more mediocre work 18:42 The number one reason clients churn, and it isn't performance 19:36 Why elimination beats automation 20:06 We're Not Recording: what else is worth your time right now 21:22 Logging scheduled tasks so AI spots trends across your client base 23:20 The prompt that stops AI from being sycophantic 24:29 Why every landing page looks the same, and why brand is now a moat 26:16 Moving from siloed AI wins to organizational effectiveness 28:53 The rise of the in-house AI integrator role 29:57 Why training two AI thinkers is worse than training the whole team 31:30 Which agencies are about to eat everyone else's lunch

How to Use AI for Creative Strategy Without Killing Your Best Ideas | Matthew Gattozzi

Foxwell Digital — Wed, 19 Aug 2026 14:59:00 +0000

How should a creative team use AI for creative strategy without losing the original ideas that make ads work?

Use AI to compress the non-creative work that surrounds ideation, not the ideation itself. A creative strategist typically spends 40 to 60 percent of the day on coordination, recaps, and admin; cutting that to 20 or 30 percent buys back the hours where original ideas actually come from. Feed the model a living brand context document so it can draft, expand, and fact-check briefs and scripts, but keep the originating idea human, because an LLM predicts from rules and past patterns and will always regress toward what has already worked.

In this episode, Will Sartorius and Matthew Gattozzi of Goodo Studios break down how to use AI for creative strategy without losing the original ideas that make ads work. Matthew explains why a strategist should hand AI the coordination and admin instead of the ideation, how to build a brand context document that actually improves your outputs, and why he cancelled his ad analytics software and built his own reporting tool instead.

We discuss:

Where AI delivers real ROI in a business built on physical production
The "Matthew tokens" model for deciding what you personally should spend time on
How to cut non-creative work from 60% of a strategist's day down to 20%
What belongs in a brand context document, and how to get AI to build it with you
How to sync context documents across a team so they stay living, not stale
Why the best ideas come from being out in the world, not behind a laptop
When a creative strategist should break the rules their own context doc sets
Why he replaced his analytics SaaS with a custom tool, and what it actually tracks
How to find net-new angles that will never show up in your account data

Join the AI DTC WTF newsletter: https://www.ai-dtc-wtf.com/aidtcwtf-newsletter This episode is brought to you by Runneth from Motion: https://runneth.com Learn more about Matthew Gattozzi Goodo Studios: https://www.goodostudios.com/ LinkedIn: https://www.linkedin.com/in/matthewgattozzi/ Site: https://matthewgattozzi.com/ To connect with Andrew Foxwell reach him here Andrew@FoxwellDigital.com To connect with Will Sartorious DM him here https://x.com/will_sartorius To Connect with Thomas Moen DM him here https://x.com/thomasmoen To learn more about Foxwell Founders and conversations like this one, go here: www.foxwellfounders.com Learn more about Foxwell Digital: https://www.foxwelldigital.com All episodes: https://www.ai-dtc-wtf.com AI DTC WTF is the podcast for people who work in DTC, use AI, and want to know what is actually working right now. Every week: tactical tips, strategies, and ideas you can implement in your AI workflows to make your brand or agency more money.

Chapters 00:00 Why AI can't break creative rules 01:12 How Goodo Studios combines creative strategy and production 03:20 Where AI fits into creative strategy, and where it doesn't 05:02 The "Matthew tokens" model for protecting your best thinking 07:04 Cutting non-creative work from 60% of a strategist's day to 20% 09:04 Why the best ad ideas come from living, not prompting 11:07 How to build a brand context document that improves AI output 13:09 Using AI to draft, expand, and fact-check ad scripts 17:50 How to share and sync AI context docs across a team 20:16 Let AI interview you to build your creative filters 22:30 What taste actually is and how you develop it 27:23 Separate context docs for statics, UGC, and studio video 28:25 When a creative strategist should break the rules 31:40 Why he built his own creative analytics tool instead of paying for SaaS 35:29 Tour of the custom Meta creative reporting dashboard 38:34 How to find net-new angles the data will never show you 43:41 Why AI is retroactive and can't generate new ideas 45:43 Building a hooks library from saved ads 47:43 Getting your team to actually use the AI tools you build 49:46 Parting advice: finding harmony between AI and creativity

The Ads That Spend $1M Are Still Written By Hand | Harry Delmege

Foxwell Digital — Thu, 06 Aug 2026 05:25:00 +0000

In this episode, Andrew Foxwell and Will Sartorius talk with Harry Delmege about using AI for ad creative — specifically where it helps and where it quietly destroys your hit rate. Harry co-founded Roly Poly Digital and is best known for long-form "yapper" ads that have scaled past $1M in spend. His team uses AI heavily for execution and almost never for ideation. You'll learn why manual research still beats AI research, why AI UGC fatigues faster than real UGC, and the one quality Harry now hires creative strategists for.

We discuss:

Where AI belongs in a creative process and where it doesn't
The Claude skills Roly Poly built for yapper ads, VSLs, and native long-form
Why AI can't find the customer story your ad actually needs
Where AI creative genuinely wins: claymation, Pixar-style spots, and b-roll you could never shoot
Why AI UGC dies faster than real UGC, even when it works
What a $200K/month ad account actually looks like in 2026
Why brand owners are firing agencies over "AI slop"
How to run a manual research bounty that keeps your team's skills sharp
Why human QA is what takes an ad from a six out of ten to a nine

Subscribe to AI DTC WTF: https://www.ai-dtc-wtf.com/ Listen on Spotify: https://open.spotify.com/show/033haXJDf9RTIAJzUQY4yC This episode is sponsored by Proppel, the hiring agency that has placed more than 75 employees for Foxwell Founders members. Get 10% off your first hire when you mention the AI DTC WTF Podcast: https://www.weareproppel.com/foxwell-... This episode is brought to you by Runneth from Motion: https://runneth.com To connect with Harry Delmege DM him here https://x.com/harrydelmege_ To connect with Andrew Foxwell reach him here Andrew@FoxwellDigital.com To connect with Will Sartorious DM him here https://x.com/will_sartorius To Connect with Thomas Moen DM him here https://x.com/thomasmoen To learn more about Foxwell Founders and conversations like this one, go here: www.foxwellfounders.com Learn more about Foxwell Digital: https://www.foxwelldigital.com All episodes: https://www.ai-dtc-wtf.com

AI DTC WTF is a short, tactical podcast from Foxwell Digital about using AI to get an edge in DTC. Hosted by Andrew Foxwell, Will Sartorius, and Thomas Moen.

Chapters:

00:00 Why AI isn't making better ads yet 01:27 Where Harry Delmege uses AI and where he refuses to 03:02 The Claude skills behind yapper, VSL, and native ads 05:03 Why manually written ads still beat AI first drafts 06:51 Why AI can't mine Reddit for real customer stories 09:07 Where AI creative actually wins, and why AI UGC dies faster 12:28 What a $200K/month ad account looks like now 16:56 Why ad volume is not the game 22:16 The pendulum swinging back to direct response fundamentals 24:40 AI psychosis and the 80/20 split inside an AI-enabled agency 26:20 The one quality to hire a creative strategist for 30:43 What the best AI users will be doing a year from now 32:58 It's not the format that's crushing, it's the story 37:14 Why human QA takes an ad from a 6 to a 9 40:05 How to stop your team from getting AI-dependent 45:27 Why big brands can't get AI animation approved

How to Build an AI Agent Team for Your Marketing Agency | Tristram Dyer

Foxwell Digital — Thu, 23 Jul 2026 10:00:00 +0000

How do you build an AI agent team for a marketing agency? Tristram Dyer, CEO of Webtopia & OAKS, walks through the exact system his agency runs: fast AI that speeds humans up with MCP data connections and AI creative tools, and slow AI, a team of scheduled background agents that detect performance anomalies, pace budgets, write morning briefings, and operate Meta ads with a human approving every change.

We discuss:

Fast AI vs. slow AI: the Thinking, Fast and Slow framework for agency work
The creative workflow connecting Claude, Arcads, Claude Design, and HeyGen
Why every Webtopia employee gets a paid Claude account
The full agent roster: anomaly detector, agent 00 morning briefings, the Meta ads operator, and Mia, the Google Ads specialist
Will AI replace ad agencies, and how to incentivize a team to adopt AI
Why agentic ad buying may be only three months away

Watch the previous episode with Cody Plofker: https://www.ai-dtc-wtf.com/podcast/why-ai-ugc-is-a-trap-and-what-actually-works-cody-plofker

This episode is brought to you by Runneth from Motion: https://runneth.com Learn more about Tris and Webtopia: https://www.webtopia.co

To connect with Andrew Foxwell reach him here Andrew@FoxwellDigital.com

To connect with Will Sartorious DM him here https://x.com/will_sartorius

To Connect with Thomas Moen DM him here https://x.com/thomasmoen

To learn more about Foxwell Founders and conversations like this one, go here: www.foxwellfounders.com

Learn more about Foxwell Digital: https://www.foxwelldigital.com All episodes: https://www.ai-dtc-wtf.com

AI DTC WTF is the super practical podcast about leveraging AI to get an edge in DTC, hosted by Andrew Foxwell, Will Sartorius, and Thomas Moen.

Chapters

00:00 How to build an AI agent team for your marketing agency

01:22 Fast AI vs. slow AI: the Kahneman framework

02:23 The fast AI stack: Meta, Kaizen, and Motion MCPs

06:26 Kaizen: adding qualitative client data to the numbers

08:27 Why every employee gets a paid Claude account

09:28 Creative workflow: Claude → Arcads → Claude Design → HeyGen

11:29 Tangible results: faster decisions, happier clients

13:31 The roadmap: putting agents in founders' hands

16:33 The agent team: BigQuery warehouse and anomaly detection

18:34 Morning briefings and a self-improving agent

19:35 The Meta ads operator with human-in-the-loop

22:40 Will AI replace ad agencies?

25:46 The Cody Plofker landing page example

27:48 How to incentivize employees to use AI

30:51 Meet Mia: the Google Ads specialist agent

The AI Updates Every Media Buyer Needs Right Now: Meta, Shopify, Youtube Shorts

Foxwell Digital — Thu, 09 Jul 2026 10:00:00 +0000

Andrew Foxwell and Thomas Mowen run through the biggest AI updates hitting Meta, Shopify, and YouTube. On the Meta side, the platform is going all in on catalogs: product images can now be auto-converted into video ads, in-campaign AI editing will crop, animate, swap backgrounds, and generate text variations on your creative automatically, and Gen AI tool adoption has jumped from 1 million to 4 million advertisers in six months. Meta also rebuilt its opportunity score, rolled out a "brand memory" feature that learns your tone, look, and fonts from your ad library, added client creative sign-off inside Ads Manager, and is expanding automatic AI disclosures. The Meta Ads AI connector (MCP) now has 29 tools for reporting, campaign builds, catalogs, pixel diagnostics, audits, and benchmarking. Plus a whole bunch more that the guys get into.

Shopify announced that AI searches powered by its catalog convert at 2x scraped data, and introduced agentic storefronts, a setting that syndicates structured product data to AI models for better discoverability across SEO, AEO, and GEO. Sidekick got major upgrades including multi-step tasks with store-wide context. Norwegian clients are already seeing meaningful agentic traffic in their analytics.

On YouTube, Shorts remain underpriced for the incrementality they drive. Demand Gen now connects product feeds with live pricing from Google Merchant Center, shoppable feeds in Shorts let you tag up to 60 products per video with in-app checkout rolling out, and Google claims Shorts shopping converts 3 to 5x better than traditional pre-rolls.

The TL,DR: AI is handling production plumbing while platforms pull discovery and checkout inside their walls. The winning recipe is clean data (especially your catalog), the right creative volume, and knowing which levers to pull.

Key Takeaways

Is your product catalog quietly costing you conversions in the AI shopping era?
What happens when Meta starts cropping, animating, and rewriting your ads automatically?
Could Meta's rebuilt opportunity score already be affecting your auction performance?
Can Meta's new brand memory finally fix "off-brand" AI creative?
Are Meta Business Agents about to become a legitimate sales channel inside your DMs?
Why do Shopify catalog-powered AI searches convert at double the rate of scraped data?
Would you recognize agentic traffic in your analytics if it showed up today?
Are YouTube Shorts the most underpriced placement left in your media mix?
What would tagging 60 shoppable products per Short do to your revenue?
Should your winning Meta ads be running as YouTube Shorts right now?
Is your AI disclosure strategy ready before Meta applies one for you?

Chapters:

00:00:00 — Intro
00:01:09 — Fable is back: workflows, token-saving tips, and an 11-bug code review story
00:04:33 — Sponsor: Runneth by Motion
00:06:58 — Meta updates: catalogs, AI editing, opportunity score, brand memory
00:11:44 — AI disclosures and the Meta Ads AI connector (MCP)
00:13:45 — Meta Business Agents: AI selling in your DMs
00:15:10 — Shopify: agentic storefronts, Sidekick upgrades, analytics
00:20:20 — YouTube Shorts: Demand Gen, shoppable feeds, in-app checkout
00:23:25 — The go-forward recipe + wrap-up

This Episode is sponsored by Motion's very own Runneth. Runneth is the AI Tool that is quickly becoming the go to decision maker brands turn to when it comes to creative decisions within their ad accounts. From Creative stratigest to hook insporations and creative briefs, runneth can do it all. See the case studies and try runneth yourself https://runneth.motionapp.com/

To connect with Andrew Foxwell reach him here Andrew@FoxwellDigital.com

To connect with Will Sartorious DM him here https://x.com/will_sartorius

To Connect mith Thomas Moen DM him here https://x.com/thomasmoen

To learn more about Foxwell Founders and conversations like this one, go here: www.foxwellfounders.com

A "Summer Fling": How Anthropic's Best Model Got Pulled

Foxwell Digital — Thu, 25 Jun 2026 03:24:00 +0000

This bonus episode covers the abrupt shutdown of Claude Fable 5 (alongside Mythos 5), Anthropic's most powerful model, which lasted only three days before the U.S. government forced it offline. Host Andrew is joined by Thomas Moen from Norway, and the two unpack what happened, why it matters, and what D2C operators and agencies should do about it. The framing is blunt: if you wired anything into Fable 5 during its brief window, this episode is your fire drill.

The hosts walk through the timeline. On June 12 at 5:21 PM Eastern, Anthropic received an export control directive from the U.S. government ordering it to suspend access to Fable 5 and Mythos 5 for any foreign national inside or outside the country, including Anthropic's own foreign-national employees. Because the company could not cleanly segment access by nationality, the practical result was a full shutoff for every customer. The stated trigger was a national security concern around a jailbreak that let the model read a codebase and spot software flaws. The hosts stress that no one was hacked and no data was breached. Anthropic complied but publicly disagreed, calling it a misunderstanding, and the situation was likened to a car part being recalled mid-deployment.

From there the conversation turns critical (without getting too political). Andrew, who previously worked as a press secretary in Congress, argues that government simply moves too slowly to regulate AI at its current pace, and that pulling a single model is more PR theater than a real solution. Thomas notes the chilling effect: people he knows are now experimenting with DeepSeek and looking harder at European model options, newly aware of how unstable reliance on U.S. models can feel. They also flag the irony that Anthropic's own transparency, admitting no model is perfectly jailbreak-proof, may have handed regulators their rationale. Both agree this sets a dangerous precedent: a government can now take down a frontier model after launch.

The back half is tactical. The core lesson is that single-model dependency is now a real operational risk, on par with relying on one 3PL or one ad platform. Agencies feel it harder than brands because of scale, with one analogy of 70 clients meaning 70 fires to put out. The hosts recommend auditing all AI dependencies (prompts, workflows, MCP configs, Zaps), assigning an internal owner for AI governance, building and actually testing a fallback ladder so models are not hard-coded, keeping a manual or "caveman mode" playbook, maintaining a locked manual database in parallel with AI-driven ones, and understanding the underlying logic of your skills and SOPs rather than trusting bloated AI-written ones. Thomas advocates for open-source systems and local models as insurance. The closing takeaway is that AI is shifting from a playground into pseudo-regulated infrastructure, so contingency planning is no longer optional. To connect with Andrew Foxwell reach him here Andrew@FoxwellDigital.com

To connect with Will Sartorious DM him here https://x.com/will_sartorius

To Connect mith Thomas Moen DM him here https://x.com/thomasmoen

To learn more about Foxwell Founders and conversations like this one, go here: www.foxwellfounders.com

The 2 Skills Thomas Moen Can't Live Without

Foxwell Digital — Thu, 25 Jun 2026 02:21:00 +0000

This is a solo episode of the AI D2C WTF podcast a departure from the usual deep-dive guest interviews. Instead host, Thomas Moen goes practical and breaks down two dead-simple AI "skills" that he personally uses 10 to 15 times a day. A skill, as he explains, is just a markdown text file that Claude (or another AI agent) reads to follow a standard operating procedure, and the AI automatically knows when to invoke it.

The first skill is Grill Me, originally created by Matt Pocock and published on GitHub. It is only three sentences long and instructs the AI to interview you relentlessly about every aspect of a plan, one question at a time, until you reach a shared understanding, offering its recommended answer for each question. Though it was built for coding and development, the host has evolved it into a business and life tool. He shares how he and his business partner each ran Grill Me when deciding whether to hire a new head of agency. He surfaced 36 questions, his partner 17, and the exercise produced two markdown documents they compared to find the right path. He notes it works for anything from fixing weekly reports to deciding between a tent trip and a glamping trip.

The second skill is Handoff, also from Matt Pocock's library. It solves the context window problem. The host references the idea of a "smart zone" and a "dumb zone," where after roughly 200,000 to 300,000 tokens the AI starts to get confused and less reliable. When he feels a conversation slipping into the dumb zone, he invokes Handoff, which captures everything relevant from the current chat into a markdown file plus a short prompt that lets a fresh AI agent pick up exactly where the last one left off. The skill is about five sentences and includes instructions to save to a temp directory, reference artifacts by path rather than duplicating them, and redact sensitive information like API keys and passwords.

Websites and SaaS Products Mentioned

Claude (Anthropic) — the AI assistant the skills run on
Motion (motionapp.com) — creative analytics platform and episode sponsor
Slack — referenced as a place to receive an AI morning performance brief
Matt Pocock's skill library — the source for both the Grill Me and Handoff skills (shared via GitHub)

To connect with Andrew Foxwell reach him here Andrew@FoxwellDigital.com

To connect with Will Sartorious DM him here https://x.com/will_sartorius

To Connect mith Thomas Moen DM him here https://x.com/thomasmoen

To learn more about Foxwell Founders and conversations like this one, go here: www.foxwellfounders.com

From Persona Research to AI Media Buyer: The Full-Stack Agency Automation Playbook

Foxwell Digital — Thu, 11 Jun 2026 04:45:00 +0000

Frederick Rode, a German AI consultant transitioning from creative strategy to full-scale agency AI implementation, joins Andrew and Thomas for a detailed breakdown of the systems he's actually running. The episode opens with his Claude research agent, a no-code Claude skill wired to Foreplay (for competitor ad library scraping) and Firecrawl (for web scraping) that outputs a 10-page brand document for agency teams to review first thing when they arrive to the office. From there the conversation covers automated ad performance reporting, and the "easier version" of that same pipeline that listners can implement right away. Thomas then shares that he currently has six Mac Minis running AI media buying for 10 of his clients (still monitored by a team but working). Freddie rounds out the episode by walking through a multi-agent CRO landing page system he built in one afternoon with Claude Code, and why splitting one big agent into three specialized ones (copy, layout, CRO) produces dramatically better output. The episode closes with a candid conversation about AI adoption: agencies are excited, not scared, and the ones moving fastest are freeing employees from execution work so they can focus on analysis and strategy. Key Takeaways:

How connecting to Foreplay's MCP server via Claude is changing the way brands can analyze their competitors' ads
Why Freddie skips local file storage and auto-upload all research directly to Supabase.
The "easy version" of automated ad performance reporting, and how listeners can build this without needing direct Meta API access.
How Railway is turning a weekly Slack performance report into a $5/month automated system for agencies
The ClickUp status trigger that automatically checks ad creative for grammar errors before they ever go live
How to build a multi-agent CRO landing page system in an afternoon with Claude Code, and why three specialized agents outperform a single all-in-one agent every time

Products & Software Mentioned

Claude (Anthropic) — https://claude.ai (core model; used for skills, research agent, all downstream workflows)
Claude Code — https://claude.ai/code (used to build CRO landing page agent and grammar review automation)
Foreplay — https://foreplay.co (save and scrape Facebook ad library; one-click MCP server connection to Claude; competitor ad transcripts, video downloads, run duration)
Firecrawl — https://www.firecrawl.dev (web scraping via MCP; extracts brand pages, Trustpilot reviews, competitor sites)
Gemini (Google) — https://gemini.google.com (visual analysis of competitor ad videos via MCP; analyzes hooks, angles, text overlay, first 3 seconds)
Supabase — https://supabase.com (database for storing personas, ad performance data, copies, headlines; official Claude MCP integration)
Meta API — https://developers.facebook.com/docs/marketing-apis/ (official ad account data: spend, hook rate, ad-level performance)
Apify — https://apify.com (ad scraping tool with official Meta ad scraper; receives post links from 2-Minute Reports and downloads asset URLs, videos, images)
2-Minute Reports — https://www.2minutereports.com (Google Sheets-based ad reporting, similar to Supermetrics; scheduled auto-reports; no Meta API setup required)
Frame.io (Frame) — https://frame.io (creative review platform; API used to automate grammar/copy QC on ads the moment they hit "ready for review" in ClickUp)
ClickUp — https://clickup.com (project management; task status change to "ready for review" triggers Frame API automation)
Railway — https://railway.app (~$5/month; connects GitHub + runs scheduled script to deliver Slack performance reports automatically each week)
North Beam —

Will Sartorius's The 3-Part Framework That Tells You Exactly Which Ads to Make Next

Foxwell Digital — Thu, 04 Jun 2026 10:00:00 +0000

Co-host Will Sartorius chats with Andrew on a wide-ranging episode that opens with a hot-take roundup on the latest model drops (Claude Opus 4.8, Google Omni (Veo 3.4)), and why Google Flow's $200/month subscription might be the most slept-on deal in AI right now. Will then shifts gears and dives into his full operational playbook. He breaks down how his agency uses AI to close more enterprise deals (a proposal workflow that litterally turns a sales call recording into 14 spec ads, a gap analysis, and a competitor breakdown that's delivered same day). He then outlines the three-piece framework his team uses to generate better creative: gap analysis, time series analysis, and social listening. Andrew and will also get real about the messy details of AI and how tool costs can add-up fast, the danger of automating for automation's sake, and how to actually structure AI governance inside an agency. This episode closes with a four-bucket framework for how agencies and D2C brands should be thinking about AI as they move through 2026 and beyond. Key Takeaways

The same-day proposal workflow Will is using to close enterprise deals faster and how you can too.
Why the gap analysis the first piece of the creative puzzle and what Will's AI tool actually shows you about your ad account.
What a time series analysis is for ad creative and how you can use the Meta API to tag every ad you've ever run by persona, angle, format, and emotion.
How social listening on these platforms will change the ads you prioritize.
How Google Flow's $200/month subscription actually stacks up vs. paying per-generation on SeaDance for high-volume video work.
Why Will decided to go back to having a human editor QC every AI-generated static before it goes live.
The TRUE cost of "playing around" with AI, and how to audit if your AI projects are actually generating revenue versus just burning tokens.
How the smartest agencies thinking about AI governance and what every agency needs to build out now

Products & Software Mentioned

Claude Opus 4.8 / Claude Sonnet 4.6 (Anthropic) — https://claude.ai (used for copywriting agents, tagging historical ads, and proposal workflows)
Claude Code — https://claude.ai/code (used for proposals, landing pages, and creative workflows)
Google Omni / Veo 3 (Google) — https://deepmind.google/technologies/veo/ (video generation model)
Google Flow — https://flow.google/ ($200/month subscription unlocking Nano Banana, Veo 3.1, Veo 3.2, Omni)
Nano Banana (Google) — Google's image generation model, accessible via Google Flow
C-Dance / Sea Dance (ByteDance) — Video generation model; comparable to Google Omni but priced per generation
GPT-4o Image Generation (OpenAI) — https://openai.com (referred to as "GPT-2" for image/static generation in context)
Read.ai — https://www.read.ai (AI meeting recording and transcription)
Granola — https://www.granola.so (AI meeting notes; mentioned as comparable to Read.ai)
11 Labs (ElevenLabs) — https://elevenlabs.io (voice AI; briefly mentioned)
Meta API — https://developers.facebook.com/docs/marketing-apis/ (used to pull historical ad data)
adlib.getskipper.ai — https://adlib.getskipper.ai (Will's free gap analysis tool — enter your brand, get persona/angle/emotion gaps)
Skipper — Will's product (social listening and creative intelligence platform; referenced throughout)
NFL.ai API — Used for generating static ad images directly into Claude Code workflow
Higgsfield — https://higgsfield.ai (AI video platform; mentioned as an alternative to Google Flow)
file.ai — Referenced as a platform team uses for video and static generation
Vercel — https://vercel.com (used for spinning up landing pages quickly)
GitH...

From Prompt Engineer to AI Architect: Florian Litterst's Full Agency Playbook

Foxwell Digital — Thu, 04 Jun 2026 10:00:00 +0000

Florian Litterst, German paid social agency owner since 2012, joins the show to break down exactly how his team has wired AI into every corner of their operation. The conversation gets specific fast, from a Claude-powered agent that scrapes competitor ads from Meta's EU ad library and surfaces untested angles every 30 days, to a another that mines Trustpilot, TrustShops, and Amazon competitor reviews for creative ammunition. Florian walks through his image generation workflow using krea.ai, why he now runs AI-ready photo shoots so every product can be "prompted into any situation," and how AI-generated B-roll is solving the impossible shot problem (think: socks on a runner's feet filmed from behind). The episode closes with a forward-looking debate on where AI is taking agencies from execution focused shops toward data-connected consultancies and a unanimous take that experienced human taste is the one thing AI still can't replace. Key Takeaways

What a real competitive intelligence AI agent looks like and how you can build one using Meta's ad library, Airtable, APFI, and Claude.
Why pulling competitor negative reviews from these places are one of the most underrated sources for ad angle discovery.
How the EU's ad transparency rule actually gives European agencies a data advantage over US-based media buyers.
Why investing in "AI-ready photo shoot" is cheaper than repeatedly shooting new product content everytime
When AI-generated video becomes a liability instead of an asset
How this one site is being used to create scalable image and video workflows.
Why creative iterations are losing their value in Meta's algorithm, and what agencies should be doing with their production time instead.

Products & Software Mentioned

ChatGPT (Deep Research) — https://chat.openai.com
Claude (Anthropic) — https://claude.ai
Airtable — https://airtable.com
APFI — API wrapper/scraping tool (referenced as tool for pulling ad library and review data via API; search "APFI API tool")
OpenAI Whisper — https://openai.com/research/whisper (used for video transcription)
krea.ai — https://www.krea.ai (image and video generation platform; wrapper for Nano Banana, Sea Dance/C-Dance, and other models)
Nano Banana (Google) — Google's image generation model, accessible via krea.ai and Google Flow
Google Drive — https://drive.google.com
Slack — https://slack.com
Trustpilot — https://www.trustpilot.com
TrustShops — https://www.trustedshops.com
Amazon (reviews) — https://www.amazon.com
Supabase — https://supabase.com (mentioned as alternative to Airtable, not used by Florian)
Netlify — https://netlify.com (briefly mentioned in context of landing page creation)

To learn more about Florian and his team at Ads Venture go here: adsventure.de

To connect with Andrew Foxwell reach him here Andrew@FoxwellDigital.com To connect with Will Sartorious DM him here https://x.com/will_sartorius To Connect mith Thomas Moen DM him here https://x.com/thomasmoen To learn more about Foxwell Founders and conversations like this one, go here: www.foxwellfounders.com

Why AI UGC Is a Trap (And What Actually Works) | Cody Plofker

Foxwell Digital — Wed, 27 May 2026 18:16:00 +0000

This episode features Cody Plofker, of Jones Road Beauty, and one of the most talked-about voices in the DTC/e-commerce space. The conversation covers how Cody has turned Claude into a full-stack CRO and conversion engine, going 5-for-5 (as he puts it) on winning A/B tests with almost 10% CVR lifts each.

Cody also gets into his end-to-end workflow and how it all starts with his "customer intelligence" markdown file fed by live MCPs ( a combination of Junip reviews, RichPanel CX tickets, OuterSignal, ListenLabs, GA4, Heatmap API). He also covers how he built Jones Road's entire design system inside a GitHub markdown file so he can now one-shot landing pages at an 80% quality rate in a single session.

Andrew and Will dig in with the harder questions from why human taste still matters, why QC agents alone won't save you and how to decide whether to build a landing page first or an ad first, The episode closes on KPIs and how Cody is raising output expectations across the board and tying AI utilization directly into performance evaluations. Key Takeaways:

How a CRO intelligence process that's pulled from customer reviews, support tickets, surveys, heatmaps, and GA4 can change the quality of your test hypotheses.
What you're actually leaving on the table when relying on QC agents to catch everything in your AI output.
Why you should be building your ads & landing pages from a single brief.
How your team can go from idea to live within 24 hours to get more testing cycles and improve your overall funnel launch standard.
How to use this analysis to surface winning persona/angle/format combinations you quietly turned off a year ago.
Understanding how much of your competitive moat actually lives in the quality of data and documentation you've fed into your AI system.
When you tell your team AI adoption is mandatory and the approach that creates real behavior change.
What "best in class" output actually looks like now that AI has raised the ceiling on what a single operator can produce.

Tangible Links

JunipProduct: reviews platform with MCP filejunip.co
RichPanel: AI-powered ecommerce CX helpdesk - richpanel.com
OuterSignal: Customer intelligence and data enrichment - outersignal.com
ListenLabs: AI-moderated customer interviews and surveys - listenlabs.ai
Typeform: Survey tool - typeform.com
Granola: AI meeting notes tool - granola.ai
GitHub: Code repository - github.com
Google Trends: Trend monitoring - trends.google.com
Reddit: Community platform - Reddit.com
ClickUp: Project management software - clickup.com
Tempo: Recently launched tool mentioned as an example of commoditized software in the design/build space - WithTempo.Ai

To learn more about Cody Plofker and his team at Jones Road Beauty go here: https://x.com/codyplof https://www.jonesroadbeauty.com/

To connect With Andrew Foxwell reach him here Andrew@FoxwellDigital.com To connect with Will Sartorious DM Him Here https://x.com/will_sartorius To Connect With Thomas Moen DM him Here https://x.com/thomasmoen To learn More about The Foxwell Founders Community and the conversations, like this one being had go here: www.foxwellfounders.com

How Tori Rowe Built an AI Operating System for His Entire Agency

Foxwell Digital — Thu, 21 May 2026 15:48:00 +0000

This episode features Torii Rowe, a Foxwell Founders member and agency operator who has quietly built a near-fully automated media buying operating system using AI. Tori dives in on how he uses Claude to ingest over 9 billion rows of client data to surface creative and media buying insights no human could pull manually. He walks through standardized naming conventions as a prerequisite for querying data across all clients, along with practical advice on where media buyers should spend their time, and the 1 tool all agency owners should be using to talk through their business problems with AI before building anything. Key Takeaways

How to connect an AI model directly to your data warehouse to unlock insights without writing SQL.
What a true AI operating system for a 30+ clients actually look like
Why this one metric is a better early indicator of creative performance than click-through rate or CPM.
How standardizing their naming conventions unlocked a cross-client creative analysis that no analytics platform currently offers out of the box.
The step-by-step stack Tori uses to go from client call data, to creative brief, to AI-generated ad.
The 1 thing that Weavy (Figma Weave) actually does that other AI image tools cannot.
When to bring in real engineers versus continuing to build with Claude Code yourself.
How to prevent analysis paralysis when you have access to massive amounts of data and insights

Tangible Links:

Snowflake: Data warehouse that has its own Cortex AI model built in and a native MCP snowflake.com ↗
Airbyte: Data pipeline tool used to pull in data from all paid media platforms, Klaviyo, Attentive, and post-purchase surveys airbyte.com ↗
Weavy / Figma Weave: Node-based AI image generation pipeline tool. weave.figma.com ↗
Kai.ai: AI image generation tool used in tandem with Figma for ad creative iteration. kai.ai ↗
Gemini (Google): Used for video tagging because it can watch and analyze video content gemini.google.com ↗
Klaviyo + Attentive: Email and SMS platforms klaviyo.com ↗
WISPR Flow: Voice-to-AI tool wispr.ai ↗

To learn more about Torii Rowe and his team At DREAM Labs Agency head here: https://dreamlabsagency.com/ Https://x.com/ToriiRowe

To Connect With Andrew Foxwell reach him here Andrew@FoxwellDigital.com

To connect with Will Sartorious DM Him Here https://x.com/will_sartorius

To Connect With Thomas Moen DM him Here https://x.com/thomasmoen

To learn More about The Foxwell Founders Community and the conversations, like this one being had go here: www.foxwellfounders.com

AI DTC WTF: Stop Starting From Scratch

Foxwell Digital — Thu, 21 May 2026 15:09:00 +0000

Andrew Foxwell & Will Sartorious open with a quick roundup of what's new in AI before diving into the main interview. They cover GPT-4o's image generation model beating Gemini in a 15-ad cookoff, a new Alibaba animation model called Happy Horse for animating static ads, Claude's new design tool, a Canva feature that separates layers on AI-generated ads for editing, and a joint venture between Anthropic, Blackstone, and Goldman Sachs that signals a shift toward AI-augmented service businesses.

The interview with Grant Hushek focuses on practical AI infrastructure for teams. Grant is an AI consultant specializing in education, adoption, and implementation. The bulk of the conversation covers skill files and markdown files, what they are, how to build them, how to share them across teams, and how to iterate on them. Grant explains how he connected Fathom (his note-taker) to HubSpot to auto-update CRM records every two hours, and he shares his three-iteration framework for building high-quality skill files. The episode wraps with a debate on Cowork vs. Claude Code and a practical screen-share walkthrough Grant does live on the call.

Key Takeaways

Why this one file type is the single most important building block for getting repeatable, high-quality AI output in your business.
Why you need to be sharing AI skill files with your team so that everyone produces the same level of output.
The first four markdown files every company should create when getting started with Claude.
Why should you be talking to Claude instead of typing when building your "About Me" and voice & tone files.
How this three-iteration framework turns a bad first skill file into one you'd actually be proud to use every day.
The real difference between Cowork and Claude Code, and the one that is actually right for your team.
The Process Grant used to automatically update every CRM contact record after every call.
Why giving Claude a PDF template tanks the quality of the output it produces and the file type you should use instead.

Tangible Links from the Show:

GPT-4o (GPT Image Gen / "GPT2") - Image generation model https://openai.com/chatgpt
Happy Horse (Alibaba)Animates static AI-generated ads https://github.com/ali-vilab/MAGI-1
Seed Dance (TikTok)Previous go-to for ad animation https://seedance.tiktok.com
Claude / Claude DesignUsed to build a new website over a weekend; Claude Design mentioned for one-off projectshttps://claude.ai
Canva New layer-separation feature for AI-generated ads allows element editing https://canva.com
Fathom AI note-taker connected to HubSpot to auto-update CRM records every two hours https://fathom.video
HubSpot CRM platform that receives Fathom transcript data via automationhttps://hubspot.com
Whisper Flow Voice-to-text tool recommended for capturing voice & tone authentically when building markdown fileshttps://whisperflow.app
Vercel Deployment platform for apps built with Claude Codehttps://vercel.com
GitHub Used alongside Claude Code for spinning up landing pages https://github.com
Notion / ClickUp https://notion.so / https://clickup.com

To learn more about Grant and his team At Grant Bot head here https://x.com/GrantHushek grantbot.co

To Connect With Andrew Foxwell reach him here Andrew@FoxwellDigital.com

To connect with Will Sartorious DM Him Here https://x.com/will_sartorius

To Connect With Thomas Moen DM him Here https://x.com/thomasmoen

To learn More about The Foxwell Founders Community and the converstations, like this one being had go here: www.foxwellfounders.com

All About The AI DTC WTF Podcast

Foxwell Digital — Wed, 20 May 2026 16:31:00 +0000

Welcome to the AI DTC WTF Podcast.