It gets rid of mistakes with every update. Not many left. It has been earning more and more trust. I drove from Seattle to San Jose in one shot two years ago. Only rarely had my hand on the steering wheel. Even through smoke, fog, snow, and heavy rain.
AUTOMATION
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AI Robotics Challenges in 2030s Impact Employment and Pensions
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Additional challenges will be posed by advanced AI robotics in the 2030s and their impact upon employment and pensions funding.
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Who will finance pensions with AI robots?
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The question remains: if robots equipped with advanced AI take over a large part of work in the 2030s, who will then fund pensions?
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Cursor automates automation with new skill
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ICYMI 👀: Cursor got a new /automate Skill
— 🚨 AI News | TestingCatalog (@testingcatalog) 21 juin 2026
Automation your toil got insanely simpler over the past few years with AI.
Even Automation is Automated now 🤖 pic.twitter.com/5Z8oQ5FL8yDID YOU MISS IT? Cursor has gained a new /automate skill Automating your tedious work has become incredibly simpler in recent years thanks to AI. Even automation is now being automated
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Enterprise AI shifts from chat to action with Action Fabric
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Enterprise AI is moving from chat to action. ServiceNow’s new Action Fabric matters because it gives AI agents governed ways to execute workflows, not just read data. That is the real test for 2026:
Can your agents act with permissions, auditability, and policy guardrails? -
Why industrial AI fails in the field, not in the model
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Today, we publish an exclusive interview with Geir Engdahl, co-founder and CTO of AI at @CogniteData. A very relevant conversation about why industrial AI generally fails not at the model level, but in the field of
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New Product Raven: Self-Evolving Agent OS
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我又来剧透了
— 艾略特 (@elliotchen100) 21 juin 2026
从龙虾到爱玛氏，从爱玛氏到什么？
没错，我们马上要发布一个全新的产品：Raven。
它不是又一个「会调用很多工具」的 Agent。
它是一个会自我进化的 Agent OS。
大多数 Agent 的学习，停在技能层：多学一个工具，多记一条流程，多写一段 prompt。
Raven 不一样。… pic.twitter.com/KoO8KGMrPCHere I go again with a spoiler. From Lobster to Aimashi, from Aimashi to what? That's right, we are about to release a brand new product: Raven. It's not just another Agent that 'can call many tools'. It's a self-evolving Agent OS. Most Agents' learning stops at the skill level: learn one more tool, memorize one more process, write one more prompt. Raven is different.
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Turn any paper into running code with autoarxiv
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Turn any paper into running code.
— Akshay 🚀 (@akshay_pachaar) 21 juin 2026
Just swap arxiv → autoarxiv in the paper url.
That hands the paper to an AI agent from alphaXiv. It reads the abstract, the claims, and the linked GitHub repo, then clones the codebase and works through the usual setup pain like dependencies,… pic.twitter.com/UOPJnWdfLJTurn any paper into running code. Just swap arxiv → autoarxiv in the paper url. That hands the paper to an AI agent from alphaXiv. It reads the abstract, the claims, and the linked GitHub repo, then clones the codebase and works through the usual setup pain like dependencies,
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Three ways to run sub-agents: Fork, Teammate, Worktree
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Nowadays everyone think sub-agents are magic.
They're not. There are basically 3 ways people run them right now. 𝟭. 𝗙𝗼𝗿𝗸
The agent spins off a task, gets the result, and continues. 𝟮. 𝗧𝗲𝗮𝗺𝗺𝗮𝘁𝗲
Multiple agents work together and share context. 𝟯. 𝗪𝗼𝗿𝗸𝘁𝗿𝗲𝗲 -
End of programming, machines generate their own code
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Fin de la programmation.
— Stephane Mallard (@StephaneMallard) 21 juin 2026
Les machines qui génèrent leur propre code.
Nous y sommes. https://t.co/sO1JWjn1gNEnd of programming.
Machines that generate their own code.
We are there.