Kamal assumes you always build your own Docker image.
But what if you just want to deploy a public image like wg-easy, Plausible, or Uptime Kuma?
TIL, there's a trick using Kamal accessories + a placeholder Dockerfile.
Full setup 👇
https://t.co/xgTmdYLr7g
#kamal#rails
dipikir2 ms ini fomo banget ya. kemaren ai boom, ujug2 integrasi juga. Sekarang openclaw, bukannya kemaren gagal dengan copilotnya ya, apa yg bikin ini beda 🤔
kenapa gak organic aja??
"You can run OpenClaw inside your company now." Annoucing our work with @Microsoft to bring OpenClaw to the Microsoft and Windows ecosystems. Claws now work securly in the enterprise.
Workflows are the biggest upgrade to Claude Code’s capabilities since skills and subagents.
I dove deep into it with @sidbid to figure out best practices, examples and more. I’m particularly excited about the non-technical tasks it enables for Claude Code.
Building autonomous agents for scientific discovery? 🧬🤖
@GoogleDeepMind Science Skills is now available on GitHub. We've open-sourced this specialized toolkit to accelerate your agentic workflows with scientific grounding and higher token efficiency.
Download now ↓
https://t.co/cwp1HOeKvo
jelek. Attention nya belum sebagus opus.
tapi.. kalo yg orchestrate nya opus. m3 ini bisa > sonet. kalo orang kek saya, yg suka typo dan missing detail; m3 > haiku.
Today, we're releasing LFM2.5-8B-A1B, a device-optimized model designed to power real-life applications on phones, laptops, PCs, robots, and fast & lightweight server-side use-cases.
> 8B MoE, 1.5B active
> Expanded 128K context
> LFM2.5 flagship hybrid MoE architecture
> Trained on 38T tokens + large-scale RL
> fast, reliable tool calling, punching above its weight, comparable to models with up to 4x its size
> customizable on a single GPU for any specialized task
> LFM2 open-weight license
🧵
This is wild 🤯
Somebody finally realized AI coding agents spend half their time searching your codebase instead of actually understanding it.
So they built a local knowledge graph for Claude Code, Cursor, Codex CLI, OpenCode, and Hermes Agent.
Not another wrapper
Not another “AI devtool” landing page
An actual semantic layer that indexes your entire repo and lets agents query relationships, call graphs, routes, symbols, and dependencies instantly.
The wild part?
On real repos like VS Code, Django, Excalidraw, Tokio, and OkHttp, CodeGraph cut:
→ ~59% tokens
→ ~70% tool calls
→ ~49% execution time
→ ~35% cost
Instead of Claude Code or Codex endlessly grepping files and spawning exploration agents, they query a pre-built graph and move straight to the relevant context.
That changes the feel of AI coding completely.
Especially on larger codebases where Cursor, Claude Code, and Codex usually start drowning in file reads.
And the setup is absurdly simple:
npx @colbymchenry/codegraph
No external APIs
No cloud dependency
No weird config hell
Just local semantic intelligence for your codebase.
This is one of those repos where you instantly understand why it blew up to 14k+ stars so fast.
100% open source
Link in comments
Context engineering is the single most important area you can focus on right now.
We already have amazing models.
Agents no longer fail because models are dumb. They fail because they don't have the right context.
Here are the 4 ingredients of good context:
Transitioning Gemini CLI users to Antigravity CLI
We are unifying our efforts around a single harness and platform, Google Antigravity with four distinct surfaces:
• Antigravity 2.0
• Antigravity CLI
• Antigravity SDK
• Antigravity IDE
This will allow us to move faster and give you a streamlined experience wherever you do your best work.
Rebuilt in Go for speed, Antigravity CLI is available today and brings robust multi-agent orchestration and asynchronous workflows to your terminal.
Important things to know:
1. If you are using Gemini CLI through your Google one account (Google AI Pro or AI Ultra) or through Gemini Code Assist for individuals (free offering) we will be helping you migrate your workflows over the next 30 days.
2. No action required for Enterprise users. Enterprise plans and API keys will continue to be supported in Gemini CLI.
Read the full details in our blog post → https://t.co/IqvqDt9XLn
Google published an entire library of highly sophisticated, end-to-end agent examples.
100% open-source.
• Complete documentation
• Source code
• Ability to one-click deploy
In the video, I break down one of the coolest examples in this collection.