Music Tech Takeaways from Santa Monica: What Matters Now for Builders
Field notes for founders, creators, and early-stage investors. Practical insights from public panels and dozens of hallway conversations at Music Tectonics in the Los Angeles area.
TL;DR
B2B first, plug into pro workflows and budgets, then consider consumer when retention proves out.
Treat AI agents as a new distribution channel, publish clean APIs and intent-findable capabilities.
Durable moats came from creation-data flywheels, open standards with partners, and trusted relationships.
B2B and monetization
💼 B2B first wins in creative AI
Land inside existing tools and budgets, use enterprise proof and retention to extend runway, then expand to consumer once the graph speaks.🧮 Price on outcomes, not “AI”
Anchor plans to time saved, quality gains, and revenue impact, this is how seed leads judge traction and Series A readiness.👩🔧 Consumer monetization is hard right now
Near-term dollars sit with pros and prosumers, focus on workflows where ROI is obvious, not one-off novelty.
Distribution and the agentic shift
🤖 Design for agents, not only users
Own stable, valuable endpoints so assistants can route intent to you, clean schemas and predictable responses beat clever demos.🔎 Make your product intent-findable
Capability docs, minimal auth for read-only discovery, and crisp error semantics act like the new SEO.📣 Distribution > features
Products that created evangelists and organic loops outperformed those with extra model controls and no adoption plan.
Moats that actually held up
🧩 Marketplace + data + partners
One team reported ~200k MAU in nine months, ~160k captured models, ~3M downloads, zero paid marketing, while 35+ companies adopted the open format behind it, liquidity plus data plus partners formed the moat.🎯 Start hyper-specific to earn trust
Rights-sensitive wedges, for example instant instrumentals for sync teams, built credibility before broader rollout.🤝 Relationships are a real moat
How you enter creative industries shapes negotiations for years, shared wins and respectful workflows compound.🪙 Compensation paths built in
Where user assets train or seed features, default-on consent and payouts reduce friction and increase supply quality.
Product craft that moved the needle
✨ Ship fast delight moments
Turn a static sample into a playable instrument in seconds, generate similar-but-unique samples to keep flow state.🧪 Portfolio R&D with kill criteria
Mix quick wins and deeper bets, define when to stop a line of work to avoid roadmap thrash.⚙️ Reliability beats one more toggle
Latency, error handling, and great presets often decided adoption more than new knobs.
Fundraising reality, 2025 edition
🧭 Narrative over timing
“Done a lot with a little,” clear milestones, and a why-now tied to distribution or ROI outperformed runway pleas.🪪 Start with insiders, then broaden
Raise first from people living the problem, then bring in generalist capital once retention and usage are obvious.🧑🔧 Founder-problem fit > vision decks
Investors pressed for firsthand problem stories and current usage, big vision works once the graph supports it.💶 Check sizes with proof
Seed leads talked about 2-5M checks when there is organic traction, early business model evidence, and strong reference calls.🤝 Pick partners, not just logos
Founders who chose investors for partner quality and founder-to-VC referrals reported smoother rounds.
Data flywheels, standards, ecosystems
🔁 Creation data compounds
High-signal creation events and edits, captured with consent, fed back into models, drove the fastest product quality gains.🧩 Build on living standards
Picking an already adopted open format unlocked distribution via dozens of plugins and devices with minimal sales effort.📈 Show measurable improvement
Demo visible quality deltas, lower error rates, or time-to-result drops, not just version bumps.
Infra to watch
🆔 Identity and metadata
KYC gaps and asset ID mismatches still block payouts, teams fixing this unlock faster and fairer royalties.💸 Royalty plumbing
Clean audit trails and fewer ownership ambiguities look investable, especially where dollars sit idle.
Reality checks
🎧 Deep behavior change is the moat
Retention with a core audience beats viral novelty, build habits that stick.🎛️ Not everyone wants to compose
Broad push-button music demand remains unproven, strong demand exists for tools that make serious creators faster.🏁 Vertical platforms must monetize
Given major distribution algorithms, niche platforms need users willing to pay and clear monetization mechanics.
Founder cheat-sheet
Land B2B first, inside existing pro workflows and budgets.
Document ROI in plain numbers, time saved and quality gains.
Publish a small stable API surface, with clear capability docs.
Choose one open standard that already lives in the ecosystem, integrate deeply.
Start with a rights-sensitive wedge, expand after trust and retention.
Investor cheat-sheet
Look for evangelist loops and usage, not single demo spikes.
Favor creation-data loops with consent and payout, plus partner adoption.
Validate pricing against outcomes, not model novelty.
Do reference calls early, check retention before writing big seed checks.
What I am watching next
Agent-origin traffic as a real distribution source for creative tools.
Open formats gaining hardware and plugin adoption.
Static-to-playable workflows that keep creators in flow.
Practical identity and metadata fixes that reduce payout leakage.
B2B tools that quietly change behavior, not just ship features.
If you are building or funding in creative AI or music tech, reply or DM to trade notes, compare early signals, or discuss partner intros. Angel investors and VCs in music tech / GenAI audio, DM me for the highlights or to hear how Deep Noise is putting these ideas into practice. DM me also for early access for AI Synthesizer (text-to-sound).