The Future of Development

The pace of change is accelerating.

Photo by Hai Nguyen

This week we released a new, free tool on the Fix Music website: a clean, simple way to retrieve recording metadata- including ISRCs, artwork, release info and more- from any Spotify link, in downloadable bulk format. No login. No fee. No strings.

It’s already helping users save time and get what they need, fast. And… it was entirely built by AI.

The real story isn’t about what the tool does, it’s about how it came to exist- how AI is currently dramatically changing the landscape. This isn’t a new story, it’s just the latest chapter in the cyclical history of innovation. That building tools, solving pain points, and iterating ideas is evolving at an increasing pace.

The implications aren’t small, but transformational. This blog isn’t about a single feature- but what it signals for the music industry, for data tooling, and for anyone trying to adapt fast in an ever faster-moving world.

Pain Point to Prototype

Back in 2019, I was managing a small but growing music publishing catalogue. Like many in administrative roles, I found myself endlessly flipping between tools, sites, and spreadsheets to gather what should’ve been simple data points: What’s the ISRC for this track? What releases did it appear on? Is it live on a DSP?

Existing tools didn’t quite meet my need, so I decided to develop something bespoke- delving into the Spotify API documentation and experimenting. I was by no means a developer, but with trial & error (and a lot of surfing Stack Overflow) in a number of weeks I’d cobbled together a rough internal tool- an effective workaround that sped up a specific workflow.

As I knew the power of this data, it was an early feature to incorporate into the Fix Music platform. Publishers need recording data, but are often the last to be in the know post release. Bringing recording metadata into their workflows in a natural and automated way delivers clear value- as it did for me in 2019.

The trigger to make a public version was a conversation with my great friend féz ., who showed me some of the AI-native workflows he'd been developing at Good Feather Music.

What stood out wasn't the specific tools he was building, but his approach to leading an AI-native music company. The speed at which they were iterating, learning, and deploying new capabilities was unlike anything I'd seen in the music industry.

That mindset- the willingness to explore and test quickly by leaning into AI was the spark.

Our team also knew his use case, and we knew the data. Building a public variant of a Spotify data tool that solved pain points made sense for bringing value to customers with our other wider dataset. What took months in 2019 took minutes to deliver with AI. It was quick because we knew what we were doing, and knew what we wanted to deliver- AI just shortcut the process.

In 6 years the build cycle itself had changed- and changed more than once, let alone more than once in the last 6 months. AI took us from idea to execution faster than ever.

AI is Supercharging the Build Cycle

This is the trend to pay attention to. We are watching, in real time, how AI is collapsing the time between idea and execution. For the ‘Lean Startup’ aficionados, it's crucially increasing the pace of the build-measure-learn cycle.

The speed of execution is increasing exponentially, and there’s significant implications:

• AI is democratising development. You no longer need seasoned engineers to build powerful, user-facing tools. This is already affecting hiring policies at tech stalwarts like Meta, creating existential policy crises. If Junior devs are replaced by AI overseen by Senior devs, who will become the next generation of Senior devs?

  
  

• Technology alone is not a moat. In business terms, a "moat" is something that protects you from competition- a unique strength others can’t easily replicate. Technology has never been a moat by itself- but leveraging technology to solve pain points and integrating customer feedback quickly to make that technology more effective can be. It’s insight, speed of execution, and ability to adapt that are the defining accelerants- AI has just made this more stark.

  
  

• Stop being precious about process. This is a hard and ongoing lesson for me. Too many businesses spend months implementing new workflows and tooling, and then cling to them as if they’re permanent. The terrain is now shifting so fast that what’s “cutting edge” this quarter can be outdated by next. We need to be ready to give up our favourite systems, tools, and processes the moment something faster and better arrives- even if that is a matter of weeks. Attachment to tools will slow us down, curiosity and agility will speed us up.

  
  

• The case for open source is stronger than ever. When it’s more straightforward to build something useful, there’s a huge opportunity for teams (especially in music and media) to share tools that help others work smarter. Not every idea needs to be proprietary- open tooling lifts the baseline for everyone.

Adapt Fast or Get Left Behind

This isn’t about building hobby projects. This is about how critical operational work is evolving, and how you can leverage more value by being open to new processes, service providers and tooling that accelerate your core offering.

Across every area of the music business- whether you’re in royalties, marketing, A&R, legal or rights management- the tools you use and the speed at which you adopt them will define your competitive edge.

This has always been true, but has become more pointed with each wave of the tech innovation cycle. Business isn’t won by those with the best tech stacks or the flashiest UIs. It’s won by those who can translate needs into working tools the fastest, who incorporate feedback and iterate in days, not months, and who aren’t afraid to tear up their own playbook (particularly playbooks that have already brought success- the classic ‘Innovator’s Dilemma’).

In 2025 this starts with embracing AI, but continues with building a culture that expects change, adapts quickly, and shares generously.

Want to try the tool? It’s live here: https://www.fixmusic.ai/data-tools.

Paste in a Spotify link, get clean metadata, download it instantly.