You run @MagicPathAI inside Codex or Cursor browser like this, https://t.co/3UPaLAtygy
— Pietro Schirano (@skirano) 1 juin 2026
You run @MagicPathAI inside Codex or Cursor browser like this,
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You run @MagicPathAI inside Codex or Cursor browser like this, https://t.co/3UPaLAtygy
— Pietro Schirano (@skirano) 1 juin 2026
You run @MagicPathAI inside Codex or Cursor browser like this,

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Top stories in AI today: – Startup cleans apartments in exchange for AI data
– The Rundown Roundtable: Our AI use cases
– Build a video workstation with Higgsfield and Claude
– Ex-DeepMind group tackles self-improving science AI
– 4 new AI tools, community workflows, and more

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We asked AI to fix one slow workflow. We got 19 agents, 3 councils, and a 5-stage journey ending in "Ascend." The actual fix was three index cards: fix the process, name an owner, start small. They're now in a glass case labeled "what we should have done." Instead — Agentic
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Hecho con Seedance 2.0 en Pollo AI
— Nico (@nicos_ai) 1 juin 2026
Prompt:
"Foto ultrarrealista de retransmisión deportiva de una mujer glamurosa sentada entre el
público de un estadio de fútbol abarrotado durante un partido nocturno, con un top de satén sin
mangas de cuello alto en marrón oscuro y pendientes… pic.twitter.com/yR2fWosLGM
Made with Seedance 2.0 on Pollo AI Prompt:
"Ultra-realistic sports broadcast photo of a glamorous woman sitting among the crowd of a packed football stadium during a night match, wearing a dark brown satin sleeveless turtleneck top and curls"

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Uber burned through its entire 2026 AI budget by mid-April. Four months. Gone. In December, Uber rolled out Claude Code to roughly 5,000 engineers. Internal adoption took off so fast that the company set up a leaderboard ranking teams by total AI tool usage. Per-engineer API
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WINDOWS USERS, REJOICE
— Charly Wargnier (@DataChaz) 1 juin 2026
If you've been waiting for agentic AI workflows, Hermes Agent is now natively supported on @Windows 🔥
Check out the guide from @NOUS here:
→ https://t.co/5qCZWgTlG1pic.twitter.com/fCB4UsNSF9
WINDOWS USERS, REJOICE If you've been waiting for agentic AI workflows, Hermes Agent is now natively supported on @Windows Check out the guide from @NOUS here: → https://
hermes-agent.nousresearch.com/docs/user-guid
e/windows-native
…
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4/ Why @ego_agent outperforms headless setups: → Shares your active Chrome state to skip auth loops.
→ Semantic snapshots read deeply nested iframes without̀ hallucinating. A TRUE first-class runtime for AI, not an afterthought. → https://
lite.ego.app macOS. 100% FREE.
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DUMPING 30K TOKENS OF RAW HTML INTO AN LLM RUINS CONTEXT AND BURNS API LIMITS.
— Charly Wargnier (@DataChaz) 1 juin 2026
🚨 @ego_agent just fixed this.
It is a custom Chromium browser where agents read a compressed 400-token tree in parallel background Spaces.
macOS. 100% FREE 🧵↓ pic.twitter.com/rEfzu2Xgji
DUMPING 30K TOKENS OF RAW HTML INTO AN LLM RUINS CONTEXT AND BURNS API LIMITS. @ego_agent just fixed this. It is a custom Chromium browser where agents read a compressed 400-token tree in parallel background Spaces. macOS. 100% FREE ↓
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ClickUp is working on a Cowork feature 👀
— 🚨 AI News | TestingCatalog (@testingcatalog) 1 juin 2026
> Cowork can help users build, edit, and take action alongside them, and other agents at the same time
> Sessions are persistent, so context carries across the entire workday
> Multiple users can collaborate in the same Brain session… pic.twitter.com/JikuZiaBMm
ClickUp is working on a Cowork feature > Cowork can help users build, edit, and take action alongside them, and other agents at the same time > Sessions are persistent, so context carries across the entire workday > Multiple users can collaborate in the same Brain session
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YOLOE-26 turns object detection into three ways of saying "find this":
— Satya Mallick (@LearnOpenCV) 1 juin 2026
→ Text prompt (name it)
→ Visual prompt (show it)
→ Prompt-free (let the model decide)
Closed-set rigidity → open-vocabulary conversation.
Tutorial + benchmarks: https://t.co/od9zkfvMaX pic.twitter.com/t1bXsIl1HJ
YOLOE-26 turns object detection into three ways of saying "find this":
→ Text prompt (name it)
→ Visual prompt (show it)
→ Prompt-free (let the model decide)
Closed-set rigidity → open-vocabulary conversation.
Tutorial + benchmarks: https://
vist.ly/565gr