Hive: This project is supported by the @Evermind community, it's really great, highly recommended. CLI agent: Everyone is racing to develop their own memory solutions. Claude Code goes with offline "dreaming" batch processing, Hermes goes with on-site embedding, but they all
AGENTS
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Codex Goal Mode Now Available in Multiple Interfaces
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3️⃣ Goal mode is now available in the Codex app, IDE extension, and CLI.
— OpenAI (@OpenAI) 22 mai 2026
Goal mode makes Codex more hands-off, letting you set a goal that it can work towards for hours or even days. pic.twitter.com/OZ18P1YxBfGoal mode is now available in the Codex app, IDE extension, and CLI. Goal mode makes Codex more hands-off, letting you set a goal that it can work towards for hours or even days.
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Codex enables secure Mac app use from locked phone
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Highlights from today’s Codex Thursday launches: Codex can now securely use apps on your Mac from your phone, even when your Mac is locked and the screen is off. http://
developers.openai.com/codex/app/comp
uter-use#locked-use
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OpenAI integrates ChatGPT into PowerPoint for slide creation
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OPENAI : ChatGPT is now available directly in PowerPoint, allowing users to create and edit slides. PowerGPT
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Dell AI Factory: NVIDIA Platform for Enterprise AI Agents
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Our CEO Jensen Huang took the stage earlier this week with @Dell CEO @MichaelDell to unveil a major update to the Dell AI Factory with NVIDIA, the full-stack platform powering the next wave of autonomous AI agents in the enterprise. From deskside workstations to massive data
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Skills enable deterministic execution for parallel model usage
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Skills can allow you to have deterministic execution patterns, so I have a lot of minimal harnesses for repeated tasks, that way I can control outcome no matter what model I use This is extremely helpful if you have multiple endpoints / models that you want to run in parallel
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Free chatbots vs costly high-capability AI agents
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Everyone on earth will get really good chatbots for free, so thats good for democratization of AI, but really good agents that can do complex work burn thousands of times more tokens, and will be reserved for places that can afford to pay, which is bad for democratization.
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Compute limits will favor agentic AI over chatbots
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We are quite short of compute, and that is going to result in compute becoming very expensive for complex agentic workflows even as single-turn chatbots get cheaper. So the richest companies & most pressing use cases will use AI agents & everyone else will be stuck with chatbots?
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Daytona’s Agent-Native Compute Explained: AI Agents Need Composable Computers
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🆕Daytona’s Agent-Native Compute: 60ms sandboxes, 50K startups in 75 sec, 850K daily runs, RL/evals, CLI > MCP, & the end of localhost https://t.co/3sauItT6oc@daytonaio CEO @ivanburazin explains why AI agents need composable computers, how Daytona pivoted from human dev… pic.twitter.com/WGjlPJwpEr
— Latent.Space (@latentspacepod) 21 mai 2026Daytona’s Agent-Native Compute: 60ms sandboxes, 50K startups in 75 sec, 850K daily runs, RL/evals, CLI > MCP, & the end of localhost https://
latent.space/p/daytona @daytonaio CEO @ivanburazin explains why AI agents need composable computers, how Daytona pivoted from human dev -
Vibecoded App to Production-Ready AI Agent Repo
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working on a "take this vibecoded slop app and make it a production-ready, e2e tested, maintainable, parallelizable agent repo" skill. this thing ran for ~16 hours yesterday and made 103 commits all told and i ended up with exactly the same app but instead of fragile mvp it