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Agent-hop – a Rust TUI that hops a live Claude Code chat into Codex

Hacker News

Agent-hop – a Rust TUI that hops a live Claude Code chat into Codex

Hi HN! Agent-hop is a TUI which allows you to use multiple coding agents and lets you hop between agents mid-chat. So, if you are using Claude Code and you do not want to lose context in another agent, you could just hop to another agent (Codex, Pi, Grok Build, OpenCode). It initially started as a resume and search tool, but I noticed some friction in that, and so I decided to create my own TUI. How is this different from Herdr? Herdr does not allow you to hop between agents live.

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Actual performance

1points
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
99%99% 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.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
34%34% 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 · Missing: plus, platform, intuitive
34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Strong signals: started · Missing: supports, reddit linkedin, podcasting
32%32% 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 · Strong signals: chat · Missing: web3, crypto, cryptocurrency
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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