Forget everything you think you know about synthetic media. Seriously. The strategies that worked last year are now obsolete. If you're still playing by the old rules, you're already behind. I'm not here to give you a history lesson. I'm here to give you a playbook, forged from hundreds of my own failures and a few massive wins. This is the one pivot you need to make to stay ahead of the curve.
For years, I struggled with synthetic media. I made every mistake in the book. I burned through cash on projects that went nowhere. I backed founders who were brilliant but chasing the wrong ideas. It was a painful, expensive education. But it taught me something vital. Something that the mainstream narrative about AI and creativity completely misses.
I’ve been lucky enough to have a couple of successful exits, with RemoteTeam being acquired by Gusto and MovieLaLa by Gfycat. I’ve also had the privilege of angel investing in over 200 companies, including some of the names you see in the headlines every day, like Anthropic, OpenAI, Scale AI, and Hugging Face. My journey has given me a front-row seat to the AI revolution, and I can tell you this: most people are looking at synthetic media all wrong.
The Siren Song of "Good Enough"
My first real disaster in this space was an AI music generator I backed a few years ago. The tech was impressive for its time. It could spit out royalty-free background music for videos and podcasts. The founder, a sharp engineer, was convinced we had a billion-dollar idea. The pitch was simple: why pay for stock music when you can generate something unique for a fraction of the cost?
We raised a seed round, built a slick interface, and launched. And for a while, it looked like we were right. We got a ton of sign-ups from YouTubers and small businesses. The problem was, they didn't stick around. The churn was brutal. Why? Because the music was just… okay. It was "good enough." It filled the silence, but it had no soul. It was generic. It was the audio equivalent of a stock photo of a corporate handshake.
I poured a lot of my own money into that company trying to keep it afloat. We tried everything. We added more genres, more instruments, more controls. But we were just polishing a fundamentally flawed product. The company eventually folded, and I lost my entire investment. It was a tough pill to swallow, but it taught me the most important lesson of my career in this field: in the world of synthetic media, "good enough" is a death sentence.
The Pivot That Changes Everything
The mistake we made, and the mistake I see countless creators and founders making today, is trying to use AI to replace human creativity. They see it as a shortcut, a way to churn out content faster and cheaper. That’s a race to the bottom. The internet is already drowning in mediocre, soulless content. The last thing anyone needs is an AI that can produce even more of it.
The real opportunity, the pivot that changes the game, is to use AI not as a replacement, but as a collaborator. Think of it as a new type of tool, a creative partner that can augment your own skills and unlock ideas you never would have had on your own.
This isn't just a philosophical shift. It’s a practical one. It means changing your entire workflow. It means moving from a mindset of "generate and publish" to one of "ideate, iterate, and refine."
My Playbook for Creative Collaboration with AI
Here’s how I approach it now, whether I’m working on a new venture or advising one of my portfolio companies. This is the playbook I wish I had when I started.
1. AI Writing: Your Unstoppable Brainstorming Partner
I don’t use AI to write my articles or my book, "Becoming Top 1%." I use it to kickstart the process. I’ll feed a model like GPT-4 or Claude a rough idea, a jumble of thoughts, and ask it to generate a dozen different outlines. Or I’ll ask it to play devil’s advocate and argue against my core thesis. I’ll have it generate metaphors, or find surprising statistics, or rewrite a paragraph in the style of my favorite author.
- The Wrong Way: "Write a blog post about the future of AI in filmmaking."
- The Right Way: "I believe the future of AI in filmmaking is about empowering independent creators, not replacing Hollywood studios. Give me ten provocative opening hooks for an article with this theme. Then, find me three real-world examples of indie filmmakers using AI in unconventional ways. Finally, act as a skeptical film critic and give me three reasons why my thesis is wrong."
See the difference? The first is a request for a finished product. The second is the start of a conversation. It uses the AI to sharpen my own thinking.
2. AI Music: From Generic Tracks to Unique Soundscapes
After my first failed music startup, I swore off the space. But then I met a founder who was taking a completely different approach. Instead of a "one-click-and-done" generator, she was building a suite of tools for musicians. Think of it like a synthesizer, but instead of oscillators and filters, you’re manipulating high-level concepts like "mood," "tension," and "instrumental texture."
Her tool doesn’t write the song for you. It gives you a new set of instruments to play. A musician can use it to generate a unique chord progression they’d never think of, and then build a song around it. Or they can feed it a melody and have it generate a dozen different harmonization options. I invested in her company on the spot. They’re not selling "AI music." They’re selling creative augmentation for musicians.
3. AI Game Design: Prototyping at the Speed of Thought
Game development is notoriously slow and expensive. I’ve seen so many brilliant game concepts die in development hell because the team couldn’t build a playable prototype fast enough to prove the core game loop was fun. This is where AI is a total game-changer.
I’m an advisor to a small indie game studio. They use AI to generate entire game levels based on a simple sketch. They can say, "Create a swamp level with a ruined temple in the center, three hidden treasure chests, and a branching path that leads to a boss fight." The AI will generate a 3D model of the level, complete with textures and lighting, in minutes. It’s not the final level, but it’s a playable prototype. They can test the layout, the pacing, the mechanics, and iterate dozens of times in a single day. They’re not replacing their level designers. They’re giving them superpowers.
4. AI Filmmaking: The End of "Fix It in Post"
In filmmaking, the cost of a mistake on set can be astronomical. Reshoots are a nightmare. I’ve seen AI tools that can change the game. Imagine being able to change the lighting in a scene after it’s been shot. Or seamlessly remove a boom mic that accidentally dipped into the frame. Or even change an actor’s dialogue without having to do ADR (Automated Dialogue Replacement).
One of my investments, a company that came out of stealth recently, is doing just that. They use generative models to manipulate video footage in ways that seem like magic. A director can now go into post-production and say, "Make the sunset in this shot more dramatic," or "Have the actor look slightly to the left in this take." This isn’t about creating fake, deepfaked actors. It’s about giving filmmakers an unprecedented level of creative control and flexibility. It’s about fixing it in AI, not in post.
A Case Study: The $100,000 Music Video That Cost $1,000
Let me give you a concrete example of this playbook in action. A musician I know wanted to create an epic, animated music video for her new single. She had a vision for a surreal, dreamlike journey through a fantastical landscape. She got a quote from a traditional animation studio: $100,000 and a six-month production timeline. She had a budget of about $1,000.
Instead of giving up, we used my playbook. Here’s what we did:
- Ideation: We spent a day brainstorming, using ChatGPT to generate wild visual concepts and storyboards based on her lyrics.
- Asset Generation: We used Midjourney to generate hundreds of still images for the key scenes. We didn’t just type in "fantasy landscape." We got specific. "A bioluminescent forest at twilight, in the style of Studio Ghibli, with a river of liquid starlight." We iterated, refined, and upscaled the best images.
- Animation: We used a tool called Runway Gen-2 to animate the still images. We fed it the images and used text prompts to describe the camera movements and effects we wanted. "Slowly pan across the image from left to right, with a gentle shimmering effect on the river."
- Editing and Post-Production: We took the animated clips and edited them together in Adobe Premiere Pro, timing the cuts to the music. We added some extra visual effects and color grading.
The entire process took about a week of part-time work. The final result was a stunning, professional-quality music video that perfectly captured her artistic vision. It looked like a million bucks, but it cost next to nothing. She didn’t just "press a button." She was the creative director, guiding the AI at every step. She was a collaborator, not a consumer.
The Future is Crafted, Not Generated
This is the future of synthetic media. It’s not about a world filled with AI-generated content. It’s about a world where humans, armed with powerful new creative tools, can bring their visions to life in ways we’re only just beginning to imagine.
As an investor in companies at the forefront of this technology, I can tell you that the biggest breakthroughs aren’t going to come from the big labs trying to build AGI. They’re going to come from the creators, the artists, the musicians, the filmmakers, and the designers who are in the trenches, using these tools every day and pushing them to their limits.
So, stop thinking about AI as a threat or a shortcut. Start thinking of it as your new creative partner. The one that never gets tired, never runs out of ideas, and is always ready to help you make something the world has never seen before. The zero-to-hero journey in synthetic media isn’t about finding the perfect algorithm. It’s about mastering the art of collaboration with it. Now go make something amazing.
Frequently Asked Questions
What would you do differently looking back?
I'd move faster on the things that were working and cut the things that weren't sooner. Most founders, myself included, hold onto failing strategies too long because of sunk cost. Speed of learning is everything.
What was the biggest challenge in this case?
Almost always, the biggest challenge is people and alignment, not technology or strategy. Getting the right team focused on the right problem is harder than any technical challenge I've encountered.
How long did it take to see results?
Most meaningful business results take 3-6 months to materialize. Anyone promising overnight success is selling something. The companies in my portfolio that grew fastest were the ones that stayed patient and consistent.
Can these results be replicated?
The specific numbers will vary, but the underlying patterns and principles are transferable. The key is understanding the context behind the results, not just copying the tactics. Every company has unique constraints that shape what works.