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CodePress – Save $50k+ a month on Cloud Agents

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CodePress – Save $50k+ a month on Cloud Agents

Since agents have taken companies + enterprise by storm, we've been working on workflows to get the most out of agents that get work done. Along the way, we built our own agent cloud where we ping these agents from any surface we work in, like GitHub or Slack. This lets us run tons of agents at a time, and as everyone knows, running agents like this could add up in inference cost! So we built something for our agents where they can use our subscriptions that Claude Code or Codex provide us. Under the hood, they're just running the Claude Code or Codex CLI so it's not a 3rd party harness, but their harness. With this, we've been saving $50k / month on inference. As long as these labs are providing these subscription deals and your company uses cloud agents, it's a no brainer to take advantage of it. This works even for teams on Claude or Codex enterprise plans. We have other cool features like a centralized MCP, so you only need to connect MCP's once and can share it with the rest of the team, automations that run on triggers or crons, apps that you can build for internal or external use, and more. Check it out and let me know what you all think!

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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
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.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
85%85% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: apps, month, way · Missing: mobile apps, ios, personal
62%62% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
56%56% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Strong signals: subscription · Missing: arr, mrr, revenue
32%32% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
27%27% 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.

Incorrect prediction on native model

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