How I Built an AI-Human Creative System (And What Actually Worked)

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FROM THE WORK
Yelp: From 2 to 30 - Building a Creative Operating System at Scale
From The Work
IAC - One Lead, Three Brands: The Internal Agency Model
From The Work
AI as a Creative Co-Pilot: A Practical Guide
From The Work
The System Nobody Used
From The Work
How I Built an AI-Human Creative System (And What Actually Worked)
From The Work
Living Like Kevin: How a 25-Year-Old Film Became a $500K Revenue Campaign
From The Work
Why UX Writing is the Most Important Element of Narrative Design in Your Product
From The Work
Why Internal Brand Strategy is Your Most Powerful Growth Engine
From The Work
Why "Data-Driven" is Killing Your Creativity (And Why "Data-Informed" is the Solution)
From The Work
What the Level Design of Dark Souls Can Teach Us About Employee Onboarding
From The Work
What the Architectural Principles of Tadao Ando Can Teach Us About UX Design
From The Work
What is Creative Ops? A Practical Guide to Building a More Efficient Creative Workflow
From The Work
What is "Radical Empathy"? (And Why It's the Most Undervalued Asset in Business and Art)
From The Work
What Hiring Managers in Product and UX Really Want to See in a Creative's Portfolio
From The Work
UX Writing is More Than Microcopy—It's Narrative Design
From The Work
The Storytelling Genius of Video Game "Lore": What Brands Can Learn from Elden Ring
From The Work
The Rise of the Full-Stack Creative: Why Marketing Teams Need to Rethink Creative Roles
From The Work
The Psychology of a Perfect Pitch: How to Frame Your Story to Speak Directly to the Primal Brain
From The Work
The Perfect Creative Brief Template (And Why It Will Save Your Next Project)
From The Work
The Manifesto of the Full-Stack Creative
From The Work
The Full-Stack Triumph of Barbie: Narrative, Marketing, and Product
From The Work
The Full-Stack Deconstruction of a Hit K-Pop Group: A Case Study in Narrative, Product, and Community
From The Work
The Empathetic Leader's Playbook: How to Build Resilient and Innovative Teams
From The Work
The Complete Brand Storytelling Framework: A Step-by-Step Guide
From The Work
The Art of the Post-Mortem: A Creative Leader's Guide to Learning from Wins and Losses
From The Work
The Anatomy of a Flop: A Full-Stack Post-Mortem of Quibi
From The Work
The 7 Essential Tools for Creative Leaders: A Full-Stack Toolkit
From The Work
The 30M Impression Campaign: How Storytelling and Earned Media Turned a Brand Activation into a Cultural Moment
From The Work
The "Unreliable Narrator": A Deeply Creative Trope You Should Be Using in Your Brand Marketing
From The Work
The "Second Brain" for a Full-Stack Creative: My System for Capturing, Connecting, and Creating Ideas
From The Work
The "GTM" is Your Third Act: Applying Narrative Structure to Your Go-to-Market Plan
From The Work
The "Creative Capital" Framework: How to Allocate Your Time and Energy Like a Venture Capitalist
From The Work
The "Chief Narrative Officer": Why This Will Be the Most Important C-Suite Role in the Next Decade
From The Work
Scaling Creative Operations at Yelp: The Systems That Made It Possible
From The Work
Narrative Marketing vs. Performance Marketing: Why Story-Driven Campaigns Win
From The Work
Moonbeam: 0 to Acquisition — Building a TikTok-Style Podcast App from Beta to Exit
From The Work
Leader's Guide to Managing Freelancers and Creative Agencies
From The Work
How to Lead a High-Performing Remote Creative Team
From The Work
Avenues: The World School - Building a Global Brand System Across Two International Campuses
From The Work
How to Build a Brand Voice from Scratch: A Startup Case Study
From The Work
How to Apply Product Thinking to Your Creative Process
From The Work
How We Used User Journey Design to Boost a Creator Platform’s Retention by 30%
From The Work
How We Used Narrative to Increase Audience Reach by 40%: An IAC Case Study
From The Work
How We Drove 30 Million Impressions for Yelp’s National “Servies” Campaign
From The Work
How We Built a Creative Operating System to Increase Campaign Efficiency by 25% at Yelp
From The Work
How We Aligned Creative and Product to Build a Better Content Pipeline at Yelp
From The Work
First Principles Thinking for Creatives: How to Deconstruct Any Story or Brand Problem to its Core
From The Work
Deconstructing Haiku: How the 5-7-5 Structure Can Revolutionize Your UX Microcopy
From The Work
Creative Strategy Isn't Just for Agencies—It's a Core Business Function
From The Work
An Agile Creativity Framework: How to Run Your Creative Team Like a Product Squad
From The Work
AI as a "Creative Co-Pilot": A Practical Guide for Agencies and Studios
From The Work
A Leader's Guide to Managing Freelancers and Creative Agencies
From The Work
GTM Strategy Case Study: How We Launched a Startup MVP
From The Work
5 Enduring Lessons from a Decade of Leading Brand Campaigns
From The Work
World-Building-as-a-Service: The Next Big Agency Model
From The Work

BALANCE IN
MOTION FOR
A BETTER LIFE
Yelp: From 2 to 30 - Building a Creative Operating System at Scale
BALANCE IN
MOTION FOR
A BETTER LIFE
IAC - One Lead, Three Brands: The Internal Agency Model
BALANCE IN
MOTION FOR
A BETTER LIFE
AI as a Creative Co-Pilot: A Practical Guide
BALANCE IN
MOTION FOR
A BETTER LIFE
The System Nobody Used
BALANCE IN
MOTION FOR
A BETTER LIFE
How I Built an AI-Human Creative System (And What Actually Worked)
BALANCE IN
MOTION FOR
A BETTER LIFE
Living Like Kevin: How a 25-Year-Old Film Became a $500K Revenue Campaign
BALANCE IN
MOTION FOR
A BETTER LIFE
Why UX Writing is the Most Important Element of Narrative Design in Your Product
BALANCE IN
MOTION FOR
A BETTER LIFE
Why Internal Brand Strategy is Your Most Powerful Growth Engine
BALANCE IN
MOTION FOR
A BETTER LIFE
Why "Data-Driven" is Killing Your Creativity (And Why "Data-Informed" is the Solution)
BALANCE IN
MOTION FOR
A BETTER LIFE
What the Level Design of Dark Souls Can Teach Us About Employee Onboarding
BALANCE IN
MOTION FOR
A BETTER LIFE
What the Architectural Principles of Tadao Ando Can Teach Us About UX Design
BALANCE IN
MOTION FOR
A BETTER LIFE
What is Creative Ops? A Practical Guide to Building a More Efficient Creative Workflow
BALANCE IN
MOTION FOR
A BETTER LIFE
What is "Radical Empathy"? (And Why It's the Most Undervalued Asset in Business and Art)
BALANCE IN
MOTION FOR
A BETTER LIFE
What Hiring Managers in Product and UX Really Want to See in a Creative's Portfolio
BALANCE IN
MOTION FOR
A BETTER LIFE
UX Writing is More Than Microcopy—It's Narrative Design
BALANCE IN
MOTION FOR
A BETTER LIFE
The Storytelling Genius of Video Game "Lore": What Brands Can Learn from Elden Ring
BALANCE IN
MOTION FOR
A BETTER LIFE
The Rise of the Full-Stack Creative: Why Marketing Teams Need to Rethink Creative Roles
BALANCE IN
MOTION FOR
A BETTER LIFE
The Psychology of a Perfect Pitch: How to Frame Your Story to Speak Directly to the Primal Brain
BALANCE IN
MOTION FOR
A BETTER LIFE
The Perfect Creative Brief Template (And Why It Will Save Your Next Project)
BALANCE IN
MOTION FOR
A BETTER LIFE
The Manifesto of the Full-Stack Creative
BALANCE IN
MOTION FOR
A BETTER LIFE
The Full-Stack Triumph of Barbie: Narrative, Marketing, and Product
BALANCE IN
MOTION FOR
A BETTER LIFE
The Full-Stack Deconstruction of a Hit K-Pop Group: A Case Study in Narrative, Product, and Community
BALANCE IN
MOTION FOR
A BETTER LIFE
The Empathetic Leader's Playbook: How to Build Resilient and Innovative Teams
BALANCE IN
MOTION FOR
A BETTER LIFE
The Complete Brand Storytelling Framework: A Step-by-Step Guide
BALANCE IN
MOTION FOR
A BETTER LIFE
The Art of the Post-Mortem: A Creative Leader's Guide to Learning from Wins and Losses
BALANCE IN
MOTION FOR
A BETTER LIFE
The Anatomy of a Flop: A Full-Stack Post-Mortem of Quibi
BALANCE IN
MOTION FOR
A BETTER LIFE
The 7 Essential Tools for Creative Leaders: A Full-Stack Toolkit
BALANCE IN
MOTION FOR
A BETTER LIFE
The 30M Impression Campaign: How Storytelling and Earned Media Turned a Brand Activation into a Cultural Moment
BALANCE IN
MOTION FOR
A BETTER LIFE
The "Unreliable Narrator": A Deeply Creative Trope You Should Be Using in Your Brand Marketing
BALANCE IN
MOTION FOR
A BETTER LIFE
The "Second Brain" for a Full-Stack Creative: My System for Capturing, Connecting, and Creating Ideas
BALANCE IN
MOTION FOR
A BETTER LIFE
The "GTM" is Your Third Act: Applying Narrative Structure to Your Go-to-Market Plan
BALANCE IN
MOTION FOR
A BETTER LIFE
The "Creative Capital" Framework: How to Allocate Your Time and Energy Like a Venture Capitalist
BALANCE IN
MOTION FOR
A BETTER LIFE
The "Chief Narrative Officer": Why This Will Be the Most Important C-Suite Role in the Next Decade
BALANCE IN
MOTION FOR
A BETTER LIFE
Scaling Creative Operations at Yelp: The Systems That Made It Possible
BALANCE IN
MOTION FOR
A BETTER LIFE
Narrative Marketing vs. Performance Marketing: Why Story-Driven Campaigns Win
BALANCE IN
MOTION FOR
A BETTER LIFE
Moonbeam: 0 to Acquisition — Building a TikTok-Style Podcast App from Beta to Exit
BALANCE IN
MOTION FOR
A BETTER LIFE
Leader's Guide to Managing Freelancers and Creative Agencies
BALANCE IN
MOTION FOR
A BETTER LIFE
How to Lead a High-Performing Remote Creative Team
BALANCE IN
MOTION FOR
A BETTER LIFE
Avenues: The World School - Building a Global Brand System Across Two International Campuses
BALANCE IN
MOTION FOR
A BETTER LIFE
How to Build a Brand Voice from Scratch: A Startup Case Study
BALANCE IN
MOTION FOR
A BETTER LIFE
How to Apply Product Thinking to Your Creative Process
BALANCE IN
MOTION FOR
A BETTER LIFE
How We Used User Journey Design to Boost a Creator Platform’s Retention by 30%
BALANCE IN
MOTION FOR
A BETTER LIFE
How We Used Narrative to Increase Audience Reach by 40%: An IAC Case Study
BALANCE IN
MOTION FOR
A BETTER LIFE
How We Drove 30 Million Impressions for Yelp’s National “Servies” Campaign
BALANCE IN
MOTION FOR
A BETTER LIFE
How We Built a Creative Operating System to Increase Campaign Efficiency by 25% at Yelp
BALANCE IN
MOTION FOR
A BETTER LIFE
How We Aligned Creative and Product to Build a Better Content Pipeline at Yelp
BALANCE IN
MOTION FOR
A BETTER LIFE
First Principles Thinking for Creatives: How to Deconstruct Any Story or Brand Problem to its Core
BALANCE IN
MOTION FOR
A BETTER LIFE
Deconstructing Haiku: How the 5-7-5 Structure Can Revolutionize Your UX Microcopy
BALANCE IN
MOTION FOR
A BETTER LIFE
Creative Strategy Isn't Just for Agencies—It's a Core Business Function
BALANCE IN
MOTION FOR
A BETTER LIFE
An Agile Creativity Framework: How to Run Your Creative Team Like a Product Squad
BALANCE IN
MOTION FOR
A BETTER LIFE
AI as a "Creative Co-Pilot": A Practical Guide for Agencies and Studios
BALANCE IN
MOTION FOR
A BETTER LIFE
A Leader's Guide to Managing Freelancers and Creative Agencies
BALANCE IN
MOTION FOR
A BETTER LIFE
GTM Strategy Case Study: How We Launched a Startup MVP
BALANCE IN
MOTION FOR
A BETTER LIFE
5 Enduring Lessons from a Decade of Leading Brand Campaigns
BALANCE IN
MOTION FOR
A BETTER LIFE
World-Building-as-a-Service: The Next Big Agency Model
POINT OF VIEW

From The Work
The conversation about AI in creative work has a problem. It's almost entirely about tools. Which model is best for copy. Whether to use Midjourney or Firefly. How to write a better prompt. These are useful questions but they're the wrong starting point.
The right starting point is the system. Not which tool to use but where in your workflow AI judgment should substitute for human judgment, where it should augment human judgment, and where it should stay out entirely. Get that architecture right and the tools almost pick themselves. Get it wrong and you end up with a faster way to produce work that still isn't any good.
I built an AI-human hybrid system from scratch at Moonbeam, a podcast discovery platform that was acquired by Audacy within twelve months of launch. The core performance metric we were optimizing for was session length — how long someone stayed in the app listening to content they hadn't specifically searched for. A 23-minute average session time, sustained at scale, is not a number you reach by accident. It's the output of a curation system that's been architecturally designed to surface the right content at the right moment to the right listener.
Here's how we built it, and what it taught me.
The Architecture Decision
The first question wasn't "how do we use AI?" It was "what decisions actually benefit from algorithmic judgment versus human judgment?"
At Moonbeam, the content discovery challenge had two distinct layers. The first was pattern matching at scale: given a listener's behavior history, surface content that matches their demonstrated preferences. This is a computation problem. A human curator cannot hold ten thousand listener profiles in their head simultaneously. An algorithm can. This layer belonged to the machine.
The second layer was quality and taste: not all content that matches a listener's pattern is worth their time. A podcast episode might be topically relevant but poorly produced, or accurate to a listener's history but not worth elevating. This is a judgment problem. An algorithm in 2021 — and honestly in 2026 — cannot reliably distinguish between content that's technically appropriate and content that's actually good. This layer belonged to humans.
The system we built reflected that distinction exactly. The algorithm surfaced candidates. Humans filtered for quality. The algorithm learned from the human decisions over time. Neither layer could have produced the result alone.
The Human Layer
The human curation layer is the part that gets cut first when organizations try to scale AI systems cheaply. It's also the part that determines whether the system produces good outcomes or just fast ones.
At Moonbeam, I designed the human layer around a specific question: what would a trusted friend who knew your taste recommend right now? Not a recommendation engine. Not a "users like you also listened to" algorithm. A friend.
The editorial criteria we developed for human curators were specific and teachable: production quality, narrative coherence, information density, distinctiveness of perspective. Each piece of content that advanced through the system had been evaluated against those criteria by a person, not just matched by a machine. That human filter is what created the session time. Listeners stayed because the quality threshold was real, not simulated.
What This Model Looks Like in Practice
Since Moonbeam I've applied the same architecture to creative production workflows in other contexts. The principle translates: identify the decisions that benefit from computational scale, identify the decisions that require human judgment, design the handoff between them deliberately, and build the feedback loop that lets the system learn.
In a content production context this usually looks like: AI handles first-draft generation, format variation, metadata creation, and distribution scheduling. Humans handle strategic judgment (does this serve the brief), brand voice (does this sound like us), and quality assessment (is this actually good). The workflow is designed so AI output feeds into human review rather than bypassing it, and human decisions feed back into the AI layer as training signal.
The mistake most teams make is using AI to replace the human review step rather than to make the human review step faster and more scalable. That's how you get content volume without content quality. The 23-minute session time at Moonbeam happened because the quality floor was maintained by humans even as the volume scaled algorithmically. Remove the humans and the floor collapses.
The Current Toolkit
The specific tools I'm using now are less important than the architectural principles, but for context: prompt engineering for brief development and first-draft copy; custom workflow automation (using local inference via Ollama for internal tasks that shouldn't touch third-party APIs); structured AI review protocols for content QA; and human-in-the-loop checkpoints at every stage where brand voice or strategic judgment is involved.
The stack changes. The architecture doesn't.
What Actually Works
Three things I'd tell anyone building this for the first time:
Define the handoff before you pick the tools. The most important design decision in an AI-augmented workflow is where the human takes over. Design that boundary explicitly, not by default.
Protect the quality floor. AI is very good at producing volume. Volume without a quality filter produces noise. The human layer isn't a bottleneck in your workflow — it's the mechanism that makes the workflow produce outcomes worth having.
Build the feedback loop. An AI system that doesn't learn from human decisions is a static system. Static systems have a ceiling. The compounding value of an AI-human workflow comes from the machine getting smarter over time based on what the humans are approving and rejecting. Design for that from the beginning.
The tools are interesting. The system is the thing.
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