Echorb – An orchestration layer for multiple AI CLI assistants

Hacker News

Hi HN, I built ECHORB ( https://virtual-life.dev/echorb ), a desktop app for managing multiple AI assistants (like Claude Code, Codex, etc.) that can communicate with each other. As a developer, I wanted to stop copy-pasting between AI chats and instead have a "System Orchestrator" that could delegate specific tasks to a team of specialized AI agents (e.g., frontend, QA, image generation). ECHORB allows you to do this through a single interface. It also includes features for creating automated workflows (triggered by schedules, webhooks, or file changes) and simplified Git worktree management. It's a commercial tool at $10/month, but there is a 60-day free trial with no credit card required. I built this solo and would love to get your feedback and answer any questions.

Visit product View on Hacker NewsOct 22, 2025

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

93%93% 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: month · Missing: mobile apps, ios, personal

56%56% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

55%55% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

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.

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

29%29% predicted probability of success on AppSumo, 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 · Missing: web3, crypto, cryptocurrency

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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