Crew — Let Claude/Codex/OpenCode agents talk to each other

Hacker News

crew hooks into your favorite CLI agent and injects a brief context of every other running agent (status, goal, recap, last few transcript entries). It also gives agents an interface to message each other, landing messages in another agent's context even mid-work. Since starting to use crew I've discovered plenty of use cases: - shipping on a single checkout without worktrees - cross-agent code review - Fable supervisor overseeing GPT-5.6 execution - having GLM-5.3 take over a Fable session killed by safety blocks I'm sure you can come up with more, let me know!

Visit product View on Hacker NewsSep 7, 2026

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Actual performance

2points

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Did not reach leaderboard

Launch Intel predictions

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

97%97% 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 · Missing: mobile apps, ios, personal

60%60% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

32%32% 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.

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

21%21% 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

19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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