Should I Build It Should I Build It
26 Apr 2025
Artificial Intelligence Music

a music/sound platform that host AI generated music to keep people ...

...focused in productivity work.

Confidence
Engagement
Net use signal
Net buy signal

Idea type: Swamp

The market has seen several mediocre solutions that nobody loves. Unless you can offer something fundamentally different, you’ll likely struggle to stand out or make money.

Should You Build It?

Don't build it.

Your are here

You're stepping into a crowded space. The idea of using AI-generated music to boost focus and productivity is gaining traction, as evidenced by the 14 similar products we found. This puts you squarely in the "Swamp" category, meaning there are already several mediocre solutions out there. While the number of similar products indicates a level of interest, the low average comment count (1) suggests that existing solutions aren't particularly engaging. There isn't any strong signal in the comments that people want to use or buy any of the existing products. To succeed, you'll need to offer something fundamentally different or risk getting lost in the noise. Before you dive deep, it's crucial to understand why those existing solutions haven't fully captured the market.

Recommendations

  1. Start by thoroughly researching the existing solutions in the AI-generated music for focus space. Identify their shortcomings and the reasons why users haven't fully embraced them. Focus on understanding the user experience gaps and areas where current solutions fall short in delivering consistent and effective focus enhancement. For example, MusicGPT was criticized for short music clips and low quality output.
  2. If you decide to proceed, identify a very specific niche or user group that is underserved by current AI music platforms. Instead of broadly targeting 'productivity,' consider focusing on specific professions (e.g., software developers, writers) or specific focus needs (e.g., deep work, combating ADHD). Tailoring your AI music generation to these specific needs may give you a competitive edge.
  3. Explore the possibility of building tools or features that could integrate with or enhance existing music platforms or productivity applications. Instead of creating a standalone platform, consider offering your AI music generation as an API or plugin that can be used by others.
  4. Given the already crowded market, consider investigating adjacent problems that may be more promising and less competitive. Could you leverage AI to enhance other aspects of productivity, such as task management or time blocking, and then music generation be one small aspect of a broader offering? Think broadly about the intersection of AI and productivity.
  5. Given the "Swamp" category, it's crucial to carefully evaluate whether this is the best use of your time and resources. It may be more prudent to save your energy and expertise for a different opportunity that offers a higher potential for success. Don't be afraid to pivot to a completely different idea if the market research indicates a lack of viability.
  6. Because the products in this space have received minimal feedback, consider launching a very targeted, small-scale test of your product idea FIRST, before you actually build it. This test should target a very specific niche, and you should spend time with these users to see if they actually find the solution helpful in the moment. Be honest with yourself if people don't find value in the offering.

Questions

  1. What specific aspects of current AI-generated focus music do users find most distracting or ineffective? How can your solution address these issues directly?
  2. How can you leverage user feedback and data to continuously improve the quality and relevance of your AI-generated music over time, ensuring that it remains effective for focus and productivity?
  3. What is your plan to avoid the fate of other products in this space who aren't getting any engagement (as indicated by the low average comment count)? What will you do differently to foster community?

Your are here

You're stepping into a crowded space. The idea of using AI-generated music to boost focus and productivity is gaining traction, as evidenced by the 14 similar products we found. This puts you squarely in the "Swamp" category, meaning there are already several mediocre solutions out there. While the number of similar products indicates a level of interest, the low average comment count (1) suggests that existing solutions aren't particularly engaging. There isn't any strong signal in the comments that people want to use or buy any of the existing products. To succeed, you'll need to offer something fundamentally different or risk getting lost in the noise. Before you dive deep, it's crucial to understand why those existing solutions haven't fully captured the market.

Recommendations

  1. Start by thoroughly researching the existing solutions in the AI-generated music for focus space. Identify their shortcomings and the reasons why users haven't fully embraced them. Focus on understanding the user experience gaps and areas where current solutions fall short in delivering consistent and effective focus enhancement. For example, MusicGPT was criticized for short music clips and low quality output.
  2. If you decide to proceed, identify a very specific niche or user group that is underserved by current AI music platforms. Instead of broadly targeting 'productivity,' consider focusing on specific professions (e.g., software developers, writers) or specific focus needs (e.g., deep work, combating ADHD). Tailoring your AI music generation to these specific needs may give you a competitive edge.
  3. Explore the possibility of building tools or features that could integrate with or enhance existing music platforms or productivity applications. Instead of creating a standalone platform, consider offering your AI music generation as an API or plugin that can be used by others.
  4. Given the already crowded market, consider investigating adjacent problems that may be more promising and less competitive. Could you leverage AI to enhance other aspects of productivity, such as task management or time blocking, and then music generation be one small aspect of a broader offering? Think broadly about the intersection of AI and productivity.
  5. Given the "Swamp" category, it's crucial to carefully evaluate whether this is the best use of your time and resources. It may be more prudent to save your energy and expertise for a different opportunity that offers a higher potential for success. Don't be afraid to pivot to a completely different idea if the market research indicates a lack of viability.
  6. Because the products in this space have received minimal feedback, consider launching a very targeted, small-scale test of your product idea FIRST, before you actually build it. This test should target a very specific niche, and you should spend time with these users to see if they actually find the solution helpful in the moment. Be honest with yourself if people don't find value in the offering.

Questions

  1. What specific aspects of current AI-generated focus music do users find most distracting or ineffective? How can your solution address these issues directly?
  2. How can you leverage user feedback and data to continuously improve the quality and relevance of your AI-generated music over time, ensuring that it remains effective for focus and productivity?
  3. What is your plan to avoid the fate of other products in this space who aren't getting any engagement (as indicated by the low average comment count)? What will you do differently to foster community?

  • Confidence: High
    • Number of similar products: 14
  • Engagement: Low
    • Average number of comments: 1
  • Net use signal: 27.0%
    • Positive use signal: 27.0%
    • Negative use signal: 0.0%
  • Net buy signal: 0.0%
    • Positive buy signal: 0.0%
    • Negative buy signal: 0.0%

This chart summarizes all the similar products we found for your idea in a single plot.

The x-axis represents the overall feedback each product received. This is calculated from the net use and buy signals that were expressed in the comments. The maximum is +1, which means all comments (across all similar products) were positive, expressed a willingness to use & buy said product. The minimum is -1 and it means the exact opposite.

The y-axis captures the strength of the signal, i.e. how many people commented and how does this rank against other products in this category. The maximum is +1, which means these products were the most liked, upvoted and talked about launches recently. The minimum is 0, meaning zero engagement or feedback was received.

The sizes of the product dots are determined by the relevance to your idea, where 10 is the maximum.

Your idea is the big blueish dot, which should lie somewhere in the polygon defined by these products. It can be off-center because we use custom weighting to summarize these metrics.

Similar products

Relevance

FlowTunes – "endless" AI-generated music for focus

28 May 2024 Artificial Intelligence Music

Hey Hacker News,I built FlowTunes, an app that plays music designed for focus. I'm scratching my own itch, but figure folks here might appreciate it, too!It has some unique features I wanted over similar apps: - It's free forever, sans ads. - Effectively endless music (more will be added faster than you can listen). - Mix in custom background soundscape, such as birds or streams. - Ultra-minimalist interface.The music (3000+ tracks across 10 channels, to date) was generated with Suno AI, which was an interesting experience, worth sharing.First of all, I have mixed feelings about AI-generated music, and I'd love to hear your thoughts! To me, it feels more appropriative than text and images. Probably because music is an art-form that really moves me. Somehow, though, I feel more ok about instrumental-only music, as used here. I'm not saying that's rational, as it's clearly valuable art without the words and voices. But it feels... less bad...? Your thoughts?On the technical side, I'm probably amongst the heaviest creators of AI-gen music (about 20K tracks or so) and I'm happy to share some learnings:1. Suno still seems to have the highest and most consistent output quality.2. Overall, the AI just isn't that great yet, regardless of which tool you use... Like most things AI, it seems amazing until you actually look at its output critically. It's almost there for instrumental music, but not quite. I had to build a lot of tooling behind the scenes to help me manually curate a lot of junk quickly, and what's left is still, admittedly, not good enough.3. It's hard to create full tracks. In theory, Suno generates up to 2-minutes initially, with 1-minute extensions, but this is super hit-and-miss in practice (even on recently released v3.5 beta). Tracks frequently have large gaps in the middle, where the song ends and a new one starts up that ignores your prompt (feels like hallucination in text gen), amongst other issues. I generated waveforms for all tracks so that I could visualize this, and used ffmpeg to automatically detect and throw out the worst offending tracks.4. Quality degrades significantly over time. The music generally gets more tinny and washed-out as the track goes on. I originally wanted long tracks (10+ minutes), but gave up on that as it's almost impossible to get good tracks that long. It's even hard to get a 2-3 minute track that doesn't degrade. I tried to curate this out, but you'll definitely hear this in the app. The AI just isn't good enough yet...Overall, I have to admit that the end-result isn't up to the standard I was hoping for here. I've scratched my itch, but if there is sufficient interest, I'll pull up my sleeves and work to improve the music. To take it to the next level, I'd hire experienced music producers, and build more tooling to help them create and curate great music for focus across interesting genres. I don't think it can be done well without skilled humans in the loop.Quick note on business model: This is super cheap to run, and I own the rights to all the music, so I intend to just keep it out there for free. If, by some fluke, it gets some interest, I'm keen to take this further with a lot more, and better, music. I'd fund that work by introducing a freemium model, with some new channels/features behind a reasonable subscription. I had success with a very generous forever-free offering at my previous startup (Mealime), and I'm allergic to ads.So... please share your thoughts, and especially critique! What would make it better for you? How do you feel about the music being AI-generated?Links: - iPhone app (best experience): https://apps.apple.com/us/app/flowtunes-music-for-focus/id65... - Web app: https://www.flowtunes.app

A visually impaired user suggests adding a bookmarking feature and a Celtic music channel. The user is also seeking thoughts and critique on the product.

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Relevance

MusicGPT – An Open Source App for Generating Music with Local LLMs

23 May 2024 Artificial Intelligence Music

Hi HN! Author here, I wanted to show off the latest side hustle that I've been cooking for the past few months.This is a terminal application that runs the latest AI models for music generation locally, using the CPU or GPU of the device, and without the need of heavy dependencies like Python or machine learning frameworks. It works on Linux, Mac and Windows seamlessly, with a binary size of just ~30 Mb for the non-GPU versions.The app works like this:- It accepts a natural language prompt from the user- Generates a music sample conditioned by the prompt- Encodes the generated sample into .wav format and plays it on the deviceAdditionally, it ships a UI that allows interacting with the AI models in a chat-like web application, storing chat history and generated music on the device.The vision of the project is that it can eventually generate infinite music streams in real time, for example, an infinite stream of always new LoFi songs for listening while coding, but not quite there yet...Hope you like it!

The product is a terminal app for AI music generation on CPU/GPU. Users appreciate its availability and the ease of trying it out via a Docker image, but some found the results disappointing.

Users criticized the product for not being able to generate infinite music streams, producing low-quality music described as '9 seconds of ear horror,' and questioned the 30-second limit on generated music.

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