SaaS Metrics
Product Positioning & Context
Heard is a macOS voice layer for your agentic workflows. It connects to Claude Code, Codex, and Cursor and turns their output into intelligent summaries you can hear. Full commentary when your eyes are elsewhere, or silence until something errors or needs a decision. With agents run in parallel, Heard summarizes at the project level, so you hear where the work stands, not five terminals talking over each other. Pair your phone and it comes with you. Open source, free for personal use.
Related Ecosystem & Alternatives
Discover adjacent products, open-source repositories, and developer tools sharing similar technical architecture.
Deep-Dive FAQs
What is Heard?
Heard is a digital product or tool described as: Give Claude Code and Codex a voice
Where did Heard originate?
Data for Heard was aggregated directly from the Product Hunt community ecosystem, representing raw developer and early-adopter sentiment.
When was Heard publicly launched?
The initial public indexing or launch date for Heard within our tracked developer communities was recorded on July 25, 2026.
How popular is Heard?
Heard has achieved measurable traction, logging over 286 traction score and facilitating 73 recorded discussions or engagements.
Which technical categories define Heard?
Based on metadata extraction, Heard is categorized under topics such as: Productivity, Developer Tools, Artificial Intelligence.
Is Heard recognized by media or academic researchers?
Yes. It has been covered by media outlets like Hackaday. This indicates the concept has reached a level of mainstream or scientific viability beyond just developer forums.
How does the creator describe Heard?
The original author or development team describes the product as follows: "Heard is a macOS voice layer for your agentic workflows. It connects to Claude Code, Codex, and Cursor and turns their output into intelligent summaries you can hear. Full commentary when your eyes..."
Community Voice & Feedback
Running agents in parallel makes the hard-signal versus context-aware split feel like the core design choice, not just a notification feature. For the project-level summaries, how do you handle two agents reaching contradictory states, such as one reporting a successful migration while another has a failing test against the same branch? Does Heard surface the conflict as a decision point, or is reconciliation left to the underlying agent sessions?
@itskellysun makes sense, the reasoning-pass override on top of the per-session read is the part I like - a pure fixed rule table would misjudge the edge cases constantly. shipping the heuristic now and layering personal preference on top later seems like the right build order rather than trying to learn preferences from day one with no baseline behavior.
I run Claude Code daily and the output itself was never the problem, it's zoning out halfway through a long scrolling session and missing the part that actually mattered. Reading holds my attention for maybe 30 seconds before I start skimming. Hearing usually doesn't do that to me. I am definitely going to try this one.
heard is awesome :) love the audio first human computer interaction approach to agent work. this is the future!
Voice as the interface to a coding agent is more interesting than it first sounds, because the hard part isn't dictation, it's knowing when to interrupt. If I'm talking while the agent is mid-task, does it queue what I said, or does it treat it as a course correction and abandon the current step? Curious where you landed on that.
Huge congrats on the launch, @itskellysun Solving the outbound half of the agent interface is such an underrated vector. qq can we adjust a 'verbosity slider' to only hear critical errors instead of full updates?
Oh this is such a nice idea, I always miss the moment when my agent is waiting on a permission prompt and lose 20 minutes for nothing. Love that there is a near silent mode too. Does the phone pairing let you actually approve things by voice while you are away from the desk, or is it more of a listen only thing?
Congrats on the launch. The multi agent part caught my eye, giving each agent its own voice identity is a smart way to keep track of parallel sessions without staring at four terminals. How does the filtering decide what counts as a critical event versus routine noise, is that configurable per project?
The verbosity dial and the project-level summary are the right primitives for parallel work. Before I'd commit to this for real sessions, I need to understand where the session state actually lives: when the context pass holds state across the session, is that in-process memory that disappears when Heard closes, persisted locally on disk, or synced to a server? Open source positioning suggests local, but the Heard Power phone-pairing feature makes me wonder if there is a relay component once you go beyond single-machine.
Love the idea of replacing terminal watching with listening. does Heard keep historical voice summaries for later review? or is the experience designed to be entirely live?
Congrats! what inspired you to focus on spoken summaries instead of visual dashboards?was there a specific pain point that pushed you in this direction?
Congratulations on shipping!The idea of each agent having its own voice is clever.can users assign custom voices to different agents?seems like that would make them easier to distinguish.
Congratulations on the launch! 🚀Really curious about the technical side. how much system overhead does Heard add while monitoring multiple agents? is performance impacted much?
how does Heard avoid interrupting users with unnecessary voice updates? can notification frequency be configured?
Congratulations! this feels like a productivity upgrade rather than just another AI wrapper. how does Heard handle long running coding sessions? does the quality of summaries improve over time?
Discovery Source
Product Hunt Aggregated via automated community intelligence tracking.
Tech Stack Dependencies
No direct open-source NPM package mentions detected in the product documentation.
Media Tractions & Mentions
Deep Research & Science
Foundational academic research matching this product's technical positioning.