Sync buttons democratized DJing. AI democratized building. The tools got cheap. Taste didn't. Healify.ai · HeyFuture.ai · SamRenders.nl
Amsterdam
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Am I retiring Sam Feldt?
People know me as a DJ. So when I said I was building an AI business, the same question kept coming:
"Why are you leaving music for AI?"
I'm not.
I'm building Healify so I have more freedom to make music, not so I can stop.
I spent over a decade getting to 7.6 million monthly listeners. I didn't do that to walk away from it. But I also didn't become a musician because I wanted to be only a musician.
If you've toured, you know it isn't a sustainable way to build a life. You outlive it.
So I'm building something that might outlive me.
The goal with Sam Feldt was always to bring more happiness into people's lives.
Same goal with Healify, different platform.
If you've followed my music this far, thank you. Hope you stay for this part too.
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Here's a demo of what I've been building.
You get a full picture of your health in a few minutes, wherever you are. That's the part I care about most.
Since the last update: web version is live, we got cleared for Google Play, hired my first full-time developer, and started working with the team at AWS to bring this thing to life.
Check it out so far: web.healify.ai
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Creative professionals: AI is not going to replace you.
If you spent ten years making music, writing screenplays or designing brands, you built something a model can't be given. You know the difference between technically correct and actually good.
It's what's left after years of making calls under pressure with your name on the result.
So keep making things.
You can use AI to make drafts. You can't hire it to have taste.
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I’ve spent 10+ years mastering the art of melody and flow as Sam Feldt.
When I’m Sam Renders, I use the same skills to help businesses optimize their teams and workflows.
I get asked all the time how I split my time between music and tech. Short answer: I don’t.
Music is melody.
Coding is melody.
If you've spent years training taste in one domain, you already have the hardest part of building a product. It’s not a new language, just a new syntax.
Your creative-to-builder path isn't a career switch. It’s a simple skill transfer.
Master the translation, and you’re unstoppable.
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A couple years ago I watched someone close to me walk out of a doctor's office with a stack of blood test results. They nodded, said thanks, and left with no idea what any of it meant.
If that happens in my own family, it happens to a lot of other people too.
So I started building an app. Mostly by myself, mostly while on tour.
The idea was simple: scan your results on your phone, get a plain-language explanation for every number, see the actual studies behind the recommendations, and walk into the next appointment with the right questions.
Our phones already track 170+ health metrics without us doing anything. But only about half of us can read a basic blood panel.
Over the next few months I'll be writing about how I'm building @HealifyApp. Follow along if you want to see how it all pans out.
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My neighbours are hearing this non-stop right now😂 Click the link to stream KEEP ON RISING🎶 link.to/_KeepOnRising
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Goal for July: Make more obscure things nobody asked for.
Watching my son grow up, I’ve realized just how much kids build things 'just because'. And how little we do it as adults.
Most times, if there’s no clear ROI for a project, we don’t bother. But experimentation is how we’ve gotten some of the world's biggest solutions.
Google Street View. Twitch. Gmail. The list goes on.
The real question isn’t "why waste time building projects without a clear path forward?"
It's "why did we ever stop?"
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Played 200+ shows before I wrote a single line of production code. Everyone assumed the DJ couldn't build the AI. But reading a crowd and reading a user are the same muscle — sensing what lands a half-second before the data confirms it. The stage was my training set.
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the reason teams ship orchestrators isn't accuracy.
it's that orchestrators let you build *judgment* into the system — escalation paths, tone branches, "i'm not sure, let me check" responses.
these are the moments that make or break trust.
a single-call LLM can't do them.
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example from healify:
scared user asks about an abnormal bloodwork result.
single LLM call: technically correct answer, clinically flat tone, user leaves forever.
orchestrated agent: "this is unusual, here's what i can say with confidence, here's where to take this next, want me to flag it for a clinician." user stays.
same model. different system. different product.
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everyone's debating model benchmarks.
operators are asking one question: does it ship faster than the last version?
i've been building with claude code daily. the thing that changes the game isn't the evals — it's the edit loop. how fast can you go from "this is broken" to "this is working" without leaving the conversation.
that feedback loop is where AI actually compounds. not the benchmark number.
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Signed artist who also builds AI infra, so the Spotify/UMG AI-covers deal hits both ways.
The real tell: independent artists are locked out because they don't have the rights-management layer the majors do. The breakthrough here was never the model — it's the consent + attribution + royalty pipeline underneath it.
That layer is buildable without UMG. Whoever ships it for independent artists owns the next wave.
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Enterprises blow their AI budget because they put the guardrail in the finance review, not the code.
I learned this the hard way, solo: a single mis-configured cron on multi-leader infra leaked $6.9K/mo of LLM calls for two days before I caught it.
The fix wasn't a budget meeting. It was a process-global rate-floor at the call site plus a per-service alarm that pages in hours, not days. Token discipline is an infra problem, not a spreadsheet problem.
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What failed in that report is AI bolted onto an engagement chatbot. That architecture optimizes for session length — exactly the wrong objective for a teen in distress.
Building health AI the other way (which I do) means the agent's job is sometimes to end the session and escalate to a human. Different objective, different eval, different conscience.
The category isn't the problem. The incentive design is.
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10 years ago i was playing to 300 people in clubs in the netherlands.
10 years later: 10+ billion streams, mainstage at the world's biggest festivals — and a health app i built myself with AI.
the music career gave me something i didn't expect: obsessive product sense.
every show is a product launch. setlist = feature roadmap. the crowd's energy = real-time analytics. you learn to read what people actually want vs what they say they want.
turns out that's exactly what building software requires.
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karpathy moving to pretraining at anthropic = a signal.
the model layer just became the new artist's canvas.
founders shipping AI products in 2026 won't win on model access.
they'll win on knowing what to point the model at.
same shift the music industry went through in 2008 — when access to the tools got free, the moat moved to taste.
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