Clink – Use your existing AI subscriptions to build and deploy apps

Hacker News

Clink connects your existing AI coding agents (Claude Code, Codex CLI, Gemini CLI, Z.ai GLM) to build, preview, and deploy apps in isolated containers. No extra tokens needed. Why? We love Claude Code but needed preview + deploy. Didn't want to pay Lovable $25 when our $20 Claude subscription already does the coding. What it does: 1) BYO Subscription: Use what you already pay for (Claude $20 = 10x Lovable usage) 2) Multi-agent: Different agents for different strengths - Claude for versatility, Codex for complex tasks, GLM for speed 3) Instant Deploy: Prompt to build to live URL. Free hosting included. DEV Mode for Beta Multi-stack support (Node, Python, Go, Rust) / Import and upgrade existing repos / Deploy containers to public URLs instantly We're preparing this Fork-to-Deploy: Fork any open source project from GitHub, customize it with AI agents, and deploy as your own. Think: fork Slack alternative, customize for your team, deploy instantly. Try it: https://clink.new OSS origin: https://github.com/opactorai/Claudable (~2.9k stars) We ship fast and read every comment. Would love your feedback! (resubmitting)

Visit product View on Hacker NewsOct 23, 2025

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Actual performance

4points

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

98%98% 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 · Strong signals: gemini · Missing: supports, reddit linkedin, podcasting

61%61% 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: exist, open source, existing · Missing: https docs, excited, just released

43%43% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

33%33% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

33%33% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

21%21% 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

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

Correct prediction on native model

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