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Team agents that manage your CMS from Slack, WhatsApp, and Telegram

Hacker News

Team agents that manage your CMS from Slack, WhatsApp, and Telegram

Hey HN, We're Cosmic (YC W19), a headless CMS. Today we're launching Team Agents and the Cosmic Agent. Team Agents are AI-powered team members that live in Slack, WhatsApp, and Telegram. They have names, roles, persistent memory, and real capabilities. Not chatbots. Not one-off prompts. Persistent agents that work alongside your team. Here's what they can do: CONTENT AGENTS write blog posts, landing pages, and marketing copy. They generate images, add SEO metadata, and publish directly to the CMS. Message them in Slack, get a finished post back. CODE AGENTS read your codebase, create branches, write components, and open PRs on GitHub. Need a new page? Message the agent. Review the PR. Merge and deploy. COMPUTER USE AGENTS browse the web like a human. They log into Vercel Analytics, Google Search Console, Ahrefs, or any web tool. They take screenshots, extract data, and build reports. No API integrations needed. If you can see it in a browser, they can. TEAM AGENTS tie it all together. They live in your messaging channels with persistent memory. They remember past conversations, learn your preferences, delegate tasks to other agents, and run on a schedule. How we use it internally: Every week, 3 Computer Use agents log into our analytics tools in parallel. A content agent synthesizes the data into a report with prioritized action items. Our content agent uses those insights to plan what to write next. Our code agent takes technical action items and ships fixes via PR. Create content, publish it, measure performance, use the data to decide what to create next. The loop runs itself. The Cosmic Agent comes built into every project from day one. It manages content, generates images and videos, browses the web, writes code, creates agents, and builds workflows. It doesn't count against agent limits. Tech details: - AI models: Claude Sonnet 4.6 / Opus 4.6 - Browser automation: Puppeteer-based computer use - Channels: Slack, WhatsApp, Telegram, Dashboard - API: REST - Workflows: multi-step pipelines with parallel execution Blog post: https://www.cosmicjs.com/blog/introducing-team-agents-and-co... Demo video: https://youtube.com/watch?v=En55pfQq2aM Happy to answer any questions.

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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 · Strong signals: para · Missing: supports, reddit linkedin, podcasting
83%83% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: video, google, para · Missing: mobile apps, ios, personal
51%51% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, pipe, io · 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.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
27%27% 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 · 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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