Nature research paper: Towards end-to-end automation of AI research
go.nature.com/4rSOGFK [Translated from EN to English]
→ View original post on X — @sakanaailabs, 2026-03-31 16:52 UTC
AUTOMATION
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Nature Article: Complete Automation of AI Research
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The Ultimate OpenClaw Guide: 100 Hours of Setup Knowledge Shared
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I’ve spent at least 100 hours setting up, training, and working with @openclaw Read the docs. Peeked into the source code. Edited config files by hand. Walked friends though their setup. Then, I wrote down everything I know. Here it is: The Ultimate 0 > 🦞 Guide ty ty to @lennysan @nateliason @davemorin @steipete @lindsmccallum @elawless for early feedback. gl hf snap snap 🦞lennysnewsletter.com/p/openc… Lenny Rachitsky (@lennysan) OpenClaw: The complete guide @ClaireVo has just put together the definitive guide to getting started with and mastering OpenClaw. Building on our podcast episode, this post covers everything you need to know, from first install to multi-agent setups, plus the real costs and security gotchas most people skip over. Whether you’re brand new to OpenClaw or already running one, Claire’s guide will level you up. Find it here 🦞: lennysnewsletter.com/p/openc… — https://nitter.net/lennysan/status/2039002789666562165#m
→ View original post on X — @paulroetzer, 2026-03-31 16:06 UTC
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OpenClaw Complete Guide: Setup and Multi-Agent Mastery
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OpenClaw: The complete guide @ClaireVo has just put together the definitive guide to getting started with and mastering OpenClaw. Building on our podcast episode, this post covers everything you need to know, from first install to multi-agent setups, plus the real costs and
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RISE Framework Enables Robots Self-Improvement Through Imagination
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What if robots could learn complex, real-world tasks significantly faster and safer, all by just imagining? Jiazhi Yang and a team from The Chinese University of Hong Kong, Kinetix AI, and Tsinghua University just unveiled RISE. This framework lets robots self-improve by
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AI Agents Transform Database Architecture Beyond 1980s Models
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The database architecture that made sense in the 1980s doesn't hold up in a world where agents are the primary builders. The reason is that agentic development doesn't work like traditional development. AI agents now create roughly 4x more databases than human users on Lakebase.
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AI Splits Enterprises Into Fast and Slow Teams
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"Instead AI is splitting enterprises into fast-learning and slow-learning teams and is rewarding organizations that redesign work, govern risk, and turn lower software costs into more software, not less." – @mjasay infoworld.com/article/415157… [Translated from EN to English]
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Convergence Toward Continual Learning and Self-Evolving Systems
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things are converging towards continual learning and self-evolving systems.
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Unified Agent Definition Across Claude Code CrewAI OpenAI
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Absolutely, same agent definition across Claude Code, CrewAI, and OpenAI is what makes it useful
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GitAgent: Framework-Agnostic AI Agent Definition Standard
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Turn any git repo into an AI agent! GitAgent is a framework-agnostic standard that lets you define agents as git repositories. Every AI framework has its own structure. Claude Code, OpenAI, LangGraph, CrewAI, AutoGen all use different formats. You build an agent in one framework and it's locked there. No portability. No reuse. GitAgent fixes this. Your repository becomes your agent. Drop two files into a git repo (agent.yaml for the manifest, SOUL. md for identity) and it becomes a portable agent definition. Export it to any framework with adapters. You get git's workflow for free. Version control your prompts. Roll back broken changes with git revert. Fork public agents, customize them, and PR improvements back. Run gitagent validate in GitHub Actions to catch issues before deployment. The structure is flexible. Start with just agent.yaml and SOUL. md. Add skills, tools, workflows, memory, and compliance rules as you need them. Everything is optional except those two core files. It works across frameworks. Export to Claude Code, OpenAI Agents SDK, CrewAI, or as a raw system prompt. Same agent definition, different runtimes. Built for compliance. First-class support for FINRA, Federal Reserve, and SEC requirements. Segregation of duties built into the spec. Define roles, conflict matrices, and handoff workflows in agent.yaml. Link to the Github Repo in comments!
→ View original post on X — @sumanth_077, 2026-03-31 14:07 UTC
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Energy Digital Twins Drive Manufacturing Competitive Advantage
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Energy digital twins aggregate distributed energy assets across multiple factory sites and optimize grid participation in real time. For manufacturers with significant energy costs, this is not just an efficiency tool. It is becoming a direct competitive advantage as energy… pic.twitter.com/lYUK3bPcq4
— Lucian Fogoros (@fogoros) 31 mars 2026Energy digital twins aggregate distributed energy assets across multiple factory sites and optimize grid participation in real time. For manufacturers with significant energy costs, this is not just an efficiency tool. It is becoming a direct competitive advantage as energy