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vechen

@miu21590 • 4,190 subscribers

17 | metacoder, reverse engineer & Unity developer

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Anya Rossi

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People use Jev to pick a model before a task. I made it change GPT-6's reasoning effort inside Codex DURING the task. More thinking when stuck. Less for routine steps. 50% lower Astra costs in my tests. Faster runs, without breaking prompt caching.

People use Jev to pick a model before a task. I made it change GPT-6's reasoning effort inside Codex DURING the task. More thinking when stuck. Less for routine steps. 50% lower Astra costs in my tests. Faster runs, without breaking prompt caching.

641,601 次观看 • 1 个月前

Introducing Octopus OS, a reinvented agent harness. Agents can edit their own harness in the middle of a task, on their own. Unlike Harness² and similar projects, self-improvement isn’t a separate stage bolted onto the agent. The whole architecture is just the environment they work in. Over 8 months, chasing self-improvement that feels truly native, I dropped the usual agent loop entirely and designed a new architecture that works a lot like a real operating system, with a 45k-line Rust kernel holding it all together. The system state lives in JSON files: goals act as real environments where agents work, along with inputs, outputs, and custom triggers they respond to. Agents can edit all of it while they work inside. It was also built as a product from day one, not a research demo. The full desktop app took 3 months, built on top of the Codex source. The client already works, and you can use it today like any other agent, Codex included. And it’s open source.

Introducing Octopus OS, a reinvented agent harness. Agents can edit their own harness in the middle of a task, on their own. Unlike Harness² and similar projects, self-improvement isn’t a separate stage bolted onto the agent. The whole architecture is just the environment they work in. Over 8 months, chasing self-improvement that feels truly native, I dropped the usual agent loop entirely and designed a new architecture that works a lot like a real operating system, with a 45k-line Rust kernel holding it all together. The system state lives in JSON files: goals act as real environments where agents work, along with inputs, outputs, and custom triggers they respond to. Agents can edit all of it while they work inside. It was also built as a product from day one, not a research demo. The full desktop app took 3 months, built on top of the Codex source. The client already works, and you can use it today like any other agent, Codex included. And it’s open source.

171,495 次观看 • 21 天前

I updated Codex Web GPT. You can now use all your ChatGPT Web models (GPT-6 Pro, GPT-5.6 Pro...) directly inside Codex, with the full harness and their separate Web limits. The launcher now tracks Pro usage too, so you can keep an eye on it as you work. Repo in replies.

I updated Codex Web GPT. You can now use all your ChatGPT Web models (GPT-6 Pro, GPT-5.6 Pro...) directly inside Codex, with the full harness and their separate Web limits. The launcher now tracks Pro usage too, so you can keep an eye on it as you work. Repo in replies.

87,360 次观看 • 1 个月前

One month left to use your ChatGPT quota inside Codex before the limits merge. My tool lets you run Web models, including Pro, directly in Codex without spending Codex quota. If you missed it, now's a good time to try it. Repo in replies.

One month left to use your ChatGPT quota inside Codex before the limits merge. My tool lets you run Web models, including Pro, directly in Codex without spending Codex quota. If you missed it, now's a good time to try it. Repo in replies.

25,671 次观看 • 14 天前

You can simply put Luna from Web inside Codex and use it for free, unlimitedly. It uses tools and performs actions on your device with the entire Harness. And it feels absolutely natively Repo in the comments

You can simply put Luna from Web inside Codex and use it for free, unlimitedly. It uses tools and performs actions on your device with the entire Harness. And it feels absolutely natively Repo in the comments

107,592 次观看 • 2 个月前

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