CLI to build voice agents with STT/TTS/LLM in one command

Hacker News

We just released a CLI to help quickly build, test, and deploy voice AI agents straight from your development environment: npx @layercode/cli init Here’s a short video showing the flow: https://www.youtube.com/watch?v=bMFNQ5RC954 We’d love feedback from developers building agents — especially if you’re experimenting with voice. What feels smooth? What doesn't? What’s missing for your projects?

Visit product View on Hacker NewsSep 29, 2025

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

94%94% 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.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

52%52% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: video · Missing: mobile apps, ios, personal

48%48% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: just released, ide · Missing: https docs, excited, exist

38%38% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

31%31% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

20%20% predicted probability of success on AppSumo, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

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

Correct prediction on native model

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