Free open source coding models in Slack

Hacker News

Hey HN, We believe we have the easiest onboarding from signup to being able to spin up coding agents in slack like Stripe, Ramp & Coinbase. Demo of the onboarding: https://www.tella.tv/video/connecting-cord-to-slack-1-19ep Every signup gets free open source models (Kimi K2.6, Qwen 3.6, DeepSeek V4, MiniMax M2.7, Gemma 4, GLM 5.1) + $100 credit for Anthropic/OpenAI. You can also use your API keys & Codex subscription.

Visit product View on Hacker NewsMay 28, 2026

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Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, model · 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.

Hacker NewsStrong engagement from HN community · Strong signals: open source, ide, io · Missing: https docs, excited, just released

66%66% 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: video · Missing: mobile apps, ios, personal

38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

36%36% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

25%25% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

20%20% 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

19%19% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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