I started as an intern grabbing coffee for Lil Wayne.
Ten years later, I was producing for Beyoncé, Nicki Minaj, and Jason Derulo.
Platinum records. Long nights. But not sustainable with a family.
So I moved from the studio into the business side - major labels.
A&R. Marketing. Management. Publishing. Learned the machine.
That led to a $350K deal with Atlantic.
The first artist we launched? A virtual influencer.
Instead of studio time, I hired developers.
We built DSP games, did motion-capture concerts, I even got a U.S. patent for inventing playback tech.
50M streams and a Grammy nomination later, the royalty statement still said unrecouped. (wtf)
Atlantic dropped the project. It stung.
So we went direct-to-fans with hyper-targeted campaigns and community.
Made $2.5M in four months.
Lesson: build your brand, find your niche, activate your audience.
I used the same playbook for other artists and labels.
Custom digital experiences, direct-to-fan campaigns.
But soon we were an agency, and it was exhausting.
10+ releases a week. No time for artist development.
Managers and marketers scrambling for virality. Execs texting me at 2 a.m. for rollout updates. Burnout.
So I built an AI agent that gave campaign updates. Suddenly, no one was texting me.
Everyone was asking the AI.
That was the “ah-ha” moment that became https://t.co/HSSTYib16o.
Today my mission is simple:
Turn AI into Artist Intelligence. Give 50 million musicians the power of a major label in their pocket.
I believe that within 10 years, artists will be able to say to a computer:
“Here’s my song. Go make me 30% ROI and ping me when complete.”
Sounds crazy, but it’s possible.
Here’s what’s in the way right now:
• Your data isn’t set up for AI agents to use.
• Your processes block fast testing and iteration.
• Your teams are too overloaded to upskill.
That’s where Recoupable comes in. To help you win.
Every day I’m building the new music industry in public.
Sharing our research, frameworks, and case studies here (+ working with a few select companies in our Beta).
The industry is at a crossroads.
Most are scared of AI.
But I think it’s going to be awesome.
You'll get more time to do what you love.
While AI is handles the rest.
If you know how to use it.
Follow me if you want to learn about the future of the music business and how to turn AI into Artist Intelligence.
Start here → https://t.co/HSSTYib16o
I spent 3 months building an AI content engine that writes LinkedIn posts. It self-improves nightly. My manual posts still outperform it 8x. Building the engine taught me more about content than writing 100 posts manually would have.
Most AI startups are solving problems that don't exist yet. They build "AI for X" where X is a workflow that 12 people do manually. Then spend 18 months convincing those 12 people to change. We did it backwards. Started by running a label. Hit real bottlenecks. Built tools to fix them.
If you can't name 10 people who would pay for your AI tool today — not "might pay someday" but would wire money this week — you're building a demo, not a business.
The music industry spends more on data tools than ever and understands their catalog less than ever. A label with 50,000 tracks paying for 8 analytics platforms. Nobody can tell you which 500 tracks are driving growth.
Every music company I talk to has the same problem. Data everywhere. Dozens of logins. None of it talks to each other. Someone spends 4 hours every Monday copy-pasting into spreadsheets.
The takeaway: match your optimization strategy to the type of work your AI is doing. Speed improvements that work for code will slow down creative tasks. Test with your actual workload before committing to any infrastructure decision.
This matters if you're choosing infrastructure. At Recoup, our catalog analysis agents run structured queries — speculative inference helps there. But our content generation work is open-ended, so the speedup doesn't apply.