Ti

Tines 3B – safe workflow automation for when everyone builds software

Hacker News

Tines 3B – safe workflow automation for when everyone builds software

Hey HN! This is Yannick from Tines, really excited to share what we’re launching today. Tines 3B is a new product we’ve built for teams building agents, apps, and automations with AI, on top of the assumption that people are already doing this, whether or not IT or security knows about it. Finance, marketing, and more are building dashboards in Claude Code or Codex. None of it is malicious, people are doing exactly what they were asked to do. The issue is there's no easy way for that work to run securely: it ends up on a laptop or personal account, with a credential pasted directly into the code, with no one else able to see it exists. Tines 3B is where that work runs instead: everyone can still build the same way, but it executes in an environment that IT and security can actually see and control. It's code-first, describe what you want, your LLM writes the implementation, with isolated executions and credentials handled through a proxy rather than embedded in the code. Our other product has been running inside security and IT teams' most sensitive systems for the last 8 years. This is the same underlying problem (who gets access to what, and who can see it), just for a new category of builder. Our explorer edition is free forever, entirely self-serve: https://login.tines.com/saml_idp/signup

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Actual performance

27points
2comments
Made the 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.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
83%83% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: excited, exist, ide · Missing: https docs, just released, lua
73%73% 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: personal, apps, way · Missing: mobile apps, ios, entrepreneurs
42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: builder · Missing: plus, platform, intuitive
32%32% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
29%29% 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
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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