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Release AI – Talk to Your Infrastructure

Hacker News

Release AI – Talk to Your Infrastructure

Hello, Hacker News! I'm David, cofounder of Release (YCW20). Introducing Release AI, a tool designed to empower users with instant access to DevOps expertise, all without monopolizing the valuable time of our experts. Developed with the developer and engineer community in mind, Release AI takes the power of OpenAI's cutting-edge GPT-4 public LLM and augments it with DevOps knowledge. In its initial phase, Release AI offers "read-only" access to both AWS and Kubernetes. This means you can engage in insightful conversations with your AWS account and K8s infrastructure effortlessly. Looking ahead, our roadmap includes plans to integrate more tools for commonly used systems. This will enable you to automate an even broader array of your daily tasks. If you would like more info you can check-out our launch YC (it has more details, screen casts): https://www.ycombinator.com/launches/JI1-release-ai-talk-to-... Our quickstart guide: https://docs.release.com/release-ai/quickstart Signup and use it: https://beta.release.com/ai/register Please give it a try! We would love your feedback as we are enhancing Release AI, reach out to us with any feature requests or crazy ideas that Release AI could do for you. Feel free to email me at david@release.com or leave a comment, looking forward to chatting with you. Join the conversation in our Slack community and discover the future of DevOps with Release AI!

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Actual performance

143points
84comments
Made the leaderboard

Launch Intel predictions

Analyze your own launch →
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
71%71% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: slack, user, new · Missing: mac, agents, macos
68%68% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: lua, hacker news, ide · Missing: https docs, excited, just released
50%50% 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: users · Missing: plus, platform, intuitive
40%40% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: users · 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: arr · Missing: mrr, revenue, profit
11%11% 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.

Correct prediction on native model

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