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Turn every floor plan to a walkable 3D home 🤯 everything is editable, or I should say promptable! Vibe-coding of home building

This is such an interesting news! Colab-as-a-service! A running sandbox with gpu! Not just agents but how many applications can ship their computation into this. Amaz amaz amaz

To get good animations from an AI you need to get good at telling it what you want: - "stagger this list of items" - "make this animation direction-aware" - "spacial consistency", "crossfade", "layout animation", I made a motion vocabulary for this: animations.dev/vocabulary

Crawl4AI v0.8.7 is live 🚀 Mostly a security hardening release. Patched several critical Docker API issues reported responsibly by the community: pre-auth RCE, SSRF on crawl and webhook endpoints, monitor auth bypass, arbitrary file write, stored XSS, unauthenticated JS execution, and a hardcoded JWT secret. Big thanks to every researcher who disclosed. Also new: DomainMapper for full-domain URL discovery, and per-URL configs for arun_many in the Docker API. Plus a batch of fixes across markdown fidelity (mermaid, tables, chunking), deep crawl, dispatcher, LLM extraction, MCP CJK handling, stealth, and logging. If you self-host the Docker API, upgrade now: pip install -U crawl4ai Release Note: github.com/unclecode/crawl4a… Star it, use it, break it: github.com/unclecode/crawl4a… Docs: docs.crawl4ai.com C4AI Hosted version, coming soon. 😎 Live long and import crawl4ai 🖖

Today @crawl4ai again became no 1 trending OSS repository! A weekend project, now after 1.5yr, 67k stars, many active projects, and many amazing developers. I am so happy n grateful of community! Live long and import crawl4ai 🖖 btw our hosted version coming soon 😎

"You cannot govern a technology you've only been briefed on." - @VivianBala The second-order signal in this story is the one worth keeping: when a Foreign Minister ships on a Raspberry Pi, the space of possible solutions just got bigger. Problems still scale exponentially, so the answer isn't fewer developers, it's more of us, working on harder problems. And what makes this work at Pi-scale isn't a bigger model. It's better data. A small LLM fed clean, well-sourced, well-curated context will out-reason a frontier model fed sludge. Data quality is the lever, not parameter count. That's the thesis behind Context4AI - what we're building in Singapore on top of @crawl4ai: authoritative extraction first, model second. Curate the input, the rest gets cheap

Tell me who is the robot? The human has to answer this or the one made this Captcha!!!!

WTF is this Captcha!!

How do you keep Claude working until the job is done? Claude Code helps with this in a few ways, including one we shipped recently: /goal.

> Open-source models (Kimi K2.6, DeepSeek v4) are now on par with Opus/GPT-5.5 at a fraction of the cost no hitting limits constantly > The real insight isn't who "won" - it's that the moat is gone. Anyone can run frontier-quality models cheaply > The harness matters as much as the model > Benchmarks are basically broken/meaningless - the model-vs-model war is a distraction > There's no best model, just the best one for you - Windows/Mac/Linux analogy news.ycombinator.com/item?id…

Kimi K2.6 just beat Claude, GPT-5.5, and Gemini in a coding challenge thinkpol.ca/2026/04/30/an-op…

OpenAI Symphony is actually great You can 5x Coding agent outcome with it Good codebase harness Played with it past few days and here is my setup: - Playwright CLI - Boot skill - WORKFLOW.md ... Broken it down in 12 mins below so you can do the same 👇

Did you see the claude.ai/design onboarding animation? So cool! Agree?

Do u get this? I get it time to time, then I reply “continue” it works! Thinking to add in my hook to retry automatically by itself 😅 @ClaudeDevs

Introducing Claude Design by Anthropic Labs: make prototypes, slides, and one-pagers by talking to Claude. Powered by Claude Opus 4.7, our most capable vision model. Available in research preview on the Pro, Max, Team, and Enterprise plans, rolling out throughout the day.

Some useful tips for Claude Code with Opus 4.7: 1/ Auto mode (Shift Tab): skip permission prompts, let Claude run complex long tasks like deep research and refactoring without interruption 2/ /fewer-permission-prompts: scans your session history, finds safe commands that keep triggering approvals, auto-whitelists them 3/ /recap: short summary of what the agent did and what is next, useful when returning to a long session after a break 4/ /focus: hides intermediate work, shows only the final result, for when you trust the model enough to let it run. Spend mire time on planning, so detailed that then u let it go without babysitting. 4/ /effort or Effort level: Opus 4.7 uses adaptive thinking instead of budgets, tune effort up for complex tasks, down for quick ones 5/ Give Claude a way to check itself, 2-3x improvement in output quality, more important than ever with longer autonomous runs. For example, make your own custom skill that runs 1/ end-to-end tests 2/ /simplify 3/ /ultrareview 4/ send PR. One command, full cycle.

🚨 Claude Opus 4.7 is out: Read the benchmark grid carefully. 4.7 wins on tool use, computer use, MCP-Atlas. Quietly regresses vs 4.6 on agentic search and cybersec vulnerability reproduction. This release is orchestration-tuned, not raw-capability tuned. The headline once you stop staring at the orange column is Mythos Preview. 4.7 is the bridge that makes the autonomous-agent stack work today, Mythos is what is actually next.

For the developers building with Claude, a direct line from the team. Follow for changelogs, API releases, community updates, and deep dives.