Live AI music sequencing agent

Hacker News

Pretzel is an experiment in live AI agents for music. It's a web synchronized music sequencer that is controlled by an AI agent. Everyone chats with the same AI agent and hears the same music at any time. I'm no audio engineer so it's a pretty basic tune, and turns out audio is a pretty complex 3d function. I went to Google's IO hackathon yesterday without any idea of what I was going to work on. I thought of building a live DJ agent that people can tell what they feel and it would update the music live. This is like 50% of the way that vision. I've been building a Rust agent harness called [Talon]( https://github.com/impalasys/talon ) that is easy to self host on a micro VM (~100mb RAM). Pretzel connects everyone to the same session in a Talon hosted DJ agent. I'm curious what y'all think.

Visit product View on Hacker NewsMay 25, 2026

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Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, google · Missing: mac, macos, cursor

95%95% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

TrustMRRFits verified-revenue profile · Strong signals: google, way · Missing: mobile apps, ios, personal

66%66% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

57%57% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Strong signals: host · Missing: plus, platform, intuitive

46%46% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

45%45% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

21%21% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: chat, audio · Missing: web3, crypto, cryptocurrency

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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