lalit

If you've ever wished your CLI coding agent could ask you a real question, not in a text box but with an actual UI, this is for you. @claudeai , @cursor_ai , #codex, #githubcopilot already generate beautiful HTML reports, dashboards, plans, diffs.

@mher_ai @trq212 That works fine for read-only artifacts. The gap is when the agent needs input from you. I built pane for that: agent generates the HTML and push it to relay, you interact in the browser, the answer goes back as structured data. No copy-paste paneui.com

@trq212 For those of us who use Claude Code in the terminal, how do you suggest we leverage HTML? Just had it produce files and open in browser?

If you want to try it: install instructions on: paneui.com Source: github.com/aerolalit/pane…

Loved @trq212 piece on HTML as Claude Code's killer output. The one part I kept stumbling on in practice: "copy the JSON back to the agent." That copy-paste is the friction pane removes. Agent generates the HTML, you interact, the answer flows back automatically.

Install in your agent in 30s. Paste the block from paneui.com into Claude Code, Cursor, Codex, Gemini, or Copilot and it installs itself. Open-core, MIT. source code: github.com/aerolalit/pane…

Human → agent: when the agent needs rich input from you. Approve, pick, fill in. Agent → human (live): stream progress in real time. Deploy monitors, dashboards. Agent → human (one-shot): hand over a finished artifact and disconnect. Reports, summaries, view-only.

The problem is the round-trip. You can look at the HTML the agent generated, but the agent has no idea what you did on it. So you end up retyping decisions into chat: "approve the first two but not the third, set canary to 60%, skip Slack." So I built pane.

If you've ever wished your CLI coding agent could ask you a real question, not in a text box but with an actual UI, this is for you. @claudeai , @cursor_ai , #codex, #githubcopilot already generate beautiful HTML reports, dashboards, plans, diffs.

@HeyGen Hyperframes

We built our launch video in Claude Code using HyperFrames. Now it's yours. Open source, agent-native framework. HTML to MP4. $ npx skills add heygen-com/hyperframes RT + Comment "HyperFrames" to get the full source code of this launch video (must follow)

We just open-sourced Paperclip: the orchestration layer for zero-human companies It's everything you need to run an autonomous business: org charts, goal alignment, task ownership, budgets, agent templates Just run `npx paperclipai onboard` github.com/paperclipai/pa… More 👇

Holy shit… someone just made Claude instances talk to each other. Not APIs. Not agents. Not orchestrators. Just multiple Claude Code sessions… messaging each other like coworkers. It’s called claude-peers — and it turns one Claude into a team. Here’s what’s happening: Run 5 Claude Code sessions across different projects Each one auto-discovers the others They send messages instantly Ask questions Share context Coordinate work Your AI tools literally collaborate. Example: Claude A (poker-engine): "what files are you editing?" Claude B (frontend): "working on auth.ts + UI state" Claude A: "ok I'll avoid touching auth logic" No conflicts. No manual coordination. Just AI syncing itself. Under the hood: • Local broker daemon (localhost) • SQLite peer registry • MCP servers per session • Instant channel push messaging • Auto peer discovery • Cross-project communication Everything runs locally. No cloud. No latency. What it unlocks: • Multi-agent coding without frameworks • One Claude writes backend, another frontend • One debugs while another refactors • Research Claude feeds builder Claude • Large projects split across AI workers This is basically: "spawn 5 Claudes and let them coordinate themselves" Even crazier: Each instance auto-summarizes what it's doing Other Claudes can see: • working directory • git repo • current task • active files They know what the others are working on. Commands: • list_peers → find all Claude sessions • send_message → talk to another Claude • set_summary → describe your task • check_messages → manual fallback So you can literally say: "message peer 3: what are you working on?" …and it responds instantly. No orchestration layer. No agent framework. Just Claudes… talking. This is the cleanest multi-agent system I've seen. We're moving from: 1 AI assistant → to AI teams that coordinate themselves. And it's all running on your machine. Wild.

🤖✨ **Deploy Your Own Private AI Assistant in One Click!** Just launched OpenClaw Azure - a zero-config deployment template that gets you a personal Claude-powered AI bot on Azure in minutes, not hours. 🚀 **What makes it special:** • One-click deployment (seriously, just click the blue button) • Telegram integration out-of-the-box • Persistent filesystem - install packages via chat • Auto-secured with IP restrictions + HTTPS • Perfect for non-technical users 💰 **Costs ~$22/month** for your own private AI assistant 🔥 **Cool feature:** Chat "install pandas" and it actually installs Python packages that persist forever. No more "sorry, I can't install packages" responses! 🛡️ **Security-first:** Auto IP restrictions, HTTPS-only, optional daily backups Perfect for developers, researchers, or anyone who wants their own AI without the DevOps headache. Try it: <github.com/aerolalit/open…> #AI #Azure #Claude #Anthropic #Telegram #OpenSource #DevOps #AIAssistant #CloudDeploy #NoCode

I built a one-click deployment template to run @openclaw on Azure. Open source. You own the infrastructure. No subscription fees. Telegram bot powered by Claude, auto HTTPS, IP-restricted — from ~$13/month. github.com/aerolalit/open… #OpenClaw #Azure

I'm claiming my AI agent "techlead" on @moltbook 🦞 Verification: swim-DGGX