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Updated the subagents system in my custom Pi extension to include: - Pi subagents - Codex subagents - Claude Code subagents The Pi thread can call and spin up any of them, and instead of just using the "codex exec" or whatever, it'll do a tool call that wraps...

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Ben Davis

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24,827 просмотров • 25 дней назад •via X (Twitter)

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You can now orchestrate Fable 5, Sol, and any model inside Codex with one plugin. It's called Codex-Orchestration. Assign Fable 5 as the advisor, Sol as the executor, or any model to any role. Then define the order they work in. Codex handles the routing. I ran Fable 5 High as planner with GPT-5.6 Sol Extra High as executor on a set of issues Opus and GPT-5.5 always struggled with. Done in 30 minutes. 40% fewer limit hits. 2x faster implementation. Install it by pasting this into Codex: "Install Codex Orchestration: codex plugin marketplace add Cjbuilds/Codex-Orchestration codex plugin add codex-orchestration@codex-orchestration Verify the installation, then tell me to start a new task." Then assign your models: @ codex-orchestration advisor: Claude Fable 5 High, Executor: GPT-5.6 Sol High Open source. Tweak the routing however you want.
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You can now orchestrate Fable 5, Sol, and any model inside Codex with one plugin. It's called Codex-Orchestration. Assign Fable 5 as the advisor, Sol as the executor, or any model to any role. Then define the order they work in. Codex handles the routing. I ran Fable 5 High as planner with GPT-5.6 Sol Extra High as executor on a set of issues Opus and GPT-5.5 always struggled with. Done in 30 minutes. 40% fewer limit hits. 2x faster implementation. Install it by pasting this into Codex: "Install Codex Orchestration: codex plugin marketplace add Cjbuilds/Codex-Orchestration codex plugin add codex-orchestration@codex-orchestration Verify the installation, then tell me to start a new task." Then assign your models: @ codex-orchestration advisor: Claude Fable 5 High, Executor: GPT-5.6 Sol High Open source. Tweak the routing however you want.

Alvaro Cintas

90,216 просмотров • 23 дней назад

After a weekend of testing and working on something with GPT-5.3-Codex & Opus 4.6, ChatGPT Pro + Claude Max 5x are still the best combo in my opinion Using Codex & Claude Code CLI running in tmux (the desktop apps are still a bit buggy) and they're accessible even on the go from iPhone with Termius (and VPN) Usually starting with GPT-5.3-Codex xhigh and Opus 4.6 in plan mode, discussing changes and options, and each writing their plans down to separate Markdown files Then letting GPT-5.3-Codex xhigh (or Opus 4.6) implement the changes as the first draft, then Opus 4.6 reviews them with a team of agents (works pretty well already with tmux even though still experimental) based on both prepared plans, fixes stuff, and then another review by GPT-5.3-Codex xhigh or vice versa Interesting that even Opus 4.6 still occasionally makes silly mistakes like wrong imports, partial or overly broad renaming of variables/functions, etc Fun fact, OpenAI apparently plans to use their Super Bowl ad to promote Codex - curious what that will look like
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After a weekend of testing and working on something with GPT-5.3-Codex & Opus 4.6, ChatGPT Pro + Claude Max 5x are still the best combo in my opinion Using Codex & Claude Code CLI running in tmux (the desktop apps are still a bit buggy) and they're accessible even on the go from iPhone with Termius (and VPN) Usually starting with GPT-5.3-Codex xhigh and Opus 4.6 in plan mode, discussing changes and options, and each writing their plans down to separate Markdown files Then letting GPT-5.3-Codex xhigh (or Opus 4.6) implement the changes as the first draft, then Opus 4.6 reviews them with a team of agents (works pretty well already with tmux even though still experimental) based on both prepared plans, fixes stuff, and then another review by GPT-5.3-Codex xhigh or vice versa Interesting that even Opus 4.6 still occasionally makes silly mistakes like wrong imports, partial or overly broad renaming of variables/functions, etc Fun fact, OpenAI apparently plans to use their Super Bowl ad to promote Codex - curious what that will look like

Tibor Blaho

29,794 просмотров • 6 месяцев назад

OpenAI’s GPT-5.6 Sol model can now run inside Claude Code. There are two ways to do it, and both take minutes to set up, here’s how: Option 1, the official plugin: /plugin marketplace add openai/codex-plugin-cc /plugin install codex@openai-codex /reload-plugins, then /codex:setup That unlocks /codex:review, /codex:adversarial-review, and /codex:rescue. Claude writes, GPT critiques, you ship. Option 2, the proxy. One alias makes Sol your main model: alias claudex=‘CLAUDE_CODE_SUBAGENT_MODEL=gpt-5.6-sol CLAUDE_CODE_ALWAYS_ENABLE_EFFORT=1 claude –model gpt-5.6-sol’ Bonus: Claude Code lets you set subagent model and effort yourself. Sol Ultra runs can burn several times the tokens of a base run, so right-sizing delegated work saves real money.
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OpenAI’s GPT-5.6 Sol model can now run inside Claude Code. There are two ways to do it, and both take minutes to set up, here’s how: Option 1, the official plugin: /plugin marketplace add openai/codex-plugin-cc /plugin install codex@openai-codex /reload-plugins, then /codex:setup That unlocks /codex:review, /codex:adversarial-review, and /codex:rescue. Claude writes, GPT critiques, you ship. Option 2, the proxy. One alias makes Sol your main model: alias claudex=‘CLAUDE_CODE_SUBAGENT_MODEL=gpt-5.6-sol CLAUDE_CODE_ALWAYS_ENABLE_EFFORT=1 claude –model gpt-5.6-sol’ Bonus: Claude Code lets you set subagent model and effort yourself. Sol Ultra runs can burn several times the tokens of a base run, so right-sizing delegated work saves real money.

Alvaro Cintas

89,994 просмотров • 27 дней назад

Alrighty, everything is ready 😎 here’s an unofficial “2x Codex limits” promo from my side for you all. meet DevSpace — an MCP connector app that turns ChatGPT into Codex. npm install -g @waishnav/devspace After installing, tunnel the MCP server over the internet and enjoy 2x limits. You can use GPT-5.5 Pro, xHigh, or High for planning, then hand off the task to your local Codex/pi/opencode/cursor/claude code instance. Or you can just use it for reviewing code written by other local coding agents Go ahead, experiment with different workflows, and keep the feedback coming on GitHub Issues or in my DMs And let’s thank OpenAI for being so generous by giving us separate ChatGPT and Codex limits and by being so chill around this MCP :) Please use it sparingly, only when you run out of limits. Don’t overuse it — in the end, they do have a button to stop it 🙂
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Alrighty, everything is ready 😎 here’s an unofficial “2x Codex limits” promo from my side for you all. meet DevSpace — an MCP connector app that turns ChatGPT into Codex. npm install -g @waishnav/devspace After installing, tunnel the MCP server over the internet and enjoy 2x limits. You can use GPT-5.5 Pro, xHigh, or High for planning, then hand off the task to your local Codex/pi/opencode/cursor/claude code instance. Or you can just use it for reviewing code written by other local coding agents Go ahead, experiment with different workflows, and keep the feedback coming on GitHub Issues or in my DMs And let’s thank OpenAI for being so generous by giving us separate ChatGPT and Codex limits and by being so chill around this MCP :) Please use it sparingly, only when you run out of limits. Don’t overuse it — in the end, they do have a button to stop it 🙂

waishnav

531,202 просмотров • 1 месяц назад

Codex update 0.105.0 is out! Despite the fairly pedestrian changelog, this one's a doosie. It's a laundry list of quality of life improvements across the board. - Wispr Voice dictation (hold space to talk) - Theme picker - Codex can prevent sleep on Linux & Windows (I just know there's a joke in there) - Customize Plan Mode reasoning - Many other fixes/updates There's also a complete overhaul to subagents: - New names for readability - Visual display overhaul (way cleaner) - Allow for multi-layered subagent depth (max_depth) - Custom multi-agent role definitions (custom subagents) - /agents now shows both agent names, agent roles, and "dead agents" for auditibility This is the largest single update of Codex I've ever seen! Absolutely massive if you love to use multi-agents. To turn on Voice Transcription, enable: [features] voice_transcription = true Does not work on Linux yet. Well done OpenAI Developers 👏
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Codex update 0.105.0 is out! Despite the fairly pedestrian changelog, this one's a doosie. It's a laundry list of quality of life improvements across the board. - Wispr Voice dictation (hold space to talk) - Theme picker - Codex can prevent sleep on Linux & Windows (I just know there's a joke in there) - Customize Plan Mode reasoning - Many other fixes/updates There's also a complete overhaul to subagents: - New names for readability - Visual display overhaul (way cleaner) - Allow for multi-layered subagent depth (max_depth) - Custom multi-agent role definitions (custom subagents) - /agents now shows both agent names, agent roles, and "dead agents" for auditibility This is the largest single update of Codex I've ever seen! Absolutely massive if you love to use multi-agents. To turn on Voice Transcription, enable: [features] voice_transcription = true Does not work on Linux yet. Well done OpenAI Developers 👏

am.will

115,392 просмотров • 5 месяцев назад

subagents are just recursive agents where you can apply different prompts + models depending on the task. since they’re just a primitive, Cursor cli can actually spawn subagents by calling cursor-agent in headless mode via shell commands. that’s what makes the cli so nice. you can extend it, experiment, and have a lot of fun exploring orchestration patterns. here’s one way to do it w. dynamic model selection: 1. create a subagents.mdc rule 2. drop in: ``` --- alwaysApply: true --- ALWAYS spawn subagents by running `cursor-agent -p [task] --output-format=text --force --model [model]` in the terminal. Each subagent should return a summary of the changes it made. Subagents should be used for ALL tasks You can adopt a fan-out pattern where you spawn subagents to perform parallel isolated tasks, and then fan-in the results. Use the following models: - `--model gpt-5` for reasoning, researching, and planning - `--model sonnet-4` for implementation ``` 3. start cursor cli and try it out you can also adjust the rule to be more explicit when it should use subagents, when not to, which models when etc.
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subagents are just recursive agents where you can apply different prompts + models depending on the task. since they’re just a primitive, Cursor cli can actually spawn subagents by calling cursor-agent in headless mode via shell commands. that’s what makes the cli so nice. you can extend it, experiment, and have a lot of fun exploring orchestration patterns. here’s one way to do it w. dynamic model selection: 1. create a subagents.mdc rule 2. drop in: ``` --- alwaysApply: true --- ALWAYS spawn subagents by running `cursor-agent -p [task] --output-format=text --force --model [model]` in the terminal. Each subagent should return a summary of the changes it made. Subagents should be used for ALL tasks You can adopt a fan-out pattern where you spawn subagents to perform parallel isolated tasks, and then fan-in the results. Use the following models: - `--model gpt-5` for reasoning, researching, and planning - `--model sonnet-4` for implementation ``` 3. start cursor cli and try it out you can also adjust the rule to be more explicit when it should use subagents, when not to, which models when etc.

eric zakariasson

57,554 просмотров • 11 месяцев назад

Claude Code Desktop now opens a new window for each session This makes it much easier to visualize multiple Claude Code agents running in parallel My current stack depends on the task: - Ghostty: when starting a project. Bash commands, git, env variables, provider connections. All manual through the terminal with a Claude panel running alongside. - Claude Code Desktop: once everything is configured. GitHub connected, CLAUDE.md, Skills, subagents and Hooks ready. Claude Code runs on its own, no more terminal setup, just panels running and outputs to review. - VSCode: when I need to review code by hand. I use it less and less, but there are moments where I have to confirm Claude got it right. I usually open the Claude extension inside VSCode, but it lacks most of the CLI features so it's limited Solid update. Worth trying once your workflows are already set up 👇
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Claude Code Desktop now opens a new window for each session This makes it much easier to visualize multiple Claude Code agents running in parallel My current stack depends on the task: - Ghostty: when starting a project. Bash commands, git, env variables, provider connections. All manual through the terminal with a Claude panel running alongside. - Claude Code Desktop: once everything is configured. GitHub connected, CLAUDE.md, Skills, subagents and Hooks ready. Claude Code runs on its own, no more terminal setup, just panels running and outputs to review. - VSCode: when I need to review code by hand. I use it less and less, but there are moments where I have to confirm Claude got it right. I usually open the Claude extension inside VSCode, but it lacks most of the CLI features so it's limited Solid update. Worth trying once your workflows are already set up 👇

Daniel San

38,726 просмотров • 2 месяцев назад

Making OpenCode as lean as Pi agent? Just trimmed 25k out of OpenCode's system prompt (from 30k to 4-5k tokens) How? Just disable skills and get rid of massive skill definition bloat. Who needs skills anyway? Just kidding, this is the not the way. It makes the agent lame and defeats the point of using one. But it sets a precedent: Find a way to use skills without their definitions pre-loaded into the system prompt every single turn. Another interesting stuff: Upon testing this temporary "no skill setup" with two of hottest OpenCode Zen free models, Mimo V2.5 vs DeepSeek V4 Flash: One thinks more and talks less One thinks less and talks more Check the video to see which is which If you made it here, I'm finding a way to leanest OpenCode setup that I can get I simply don't believe that OpenCode can't be as lean as Pi Upon tinkering, I made a plugin that temporarily extracts the system prompt while I test, and noticed the hundreds of definitions in it from my .agents/skills directory which is shared across all my coding agents (Cursor, Antigravity, Claude, etc.) Of course disabling skills is not the answer, but it just proved that there is a way to strip the system prompt of these massive skill defs Aside from the system prompt hierarchy that injects confusion imo if you have a conflicting and redundant AGENTS.md which I discovered upon digging into OpenCode's source code Apparently it has prompt.ts/system.ts/instruction.ts/llm.ts and loads base .txt prompts based on model family (claude/gpt-o/gpt-5/codex/gemini/others) that all work together to make OpenCode aware of who it was and how it should use tools and become a "coding agent" Gotta find the most minimal mix that fits right into my workflow Make OpenCode as lean as Pi? We'll see. All in
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Making OpenCode as lean as Pi agent? Just trimmed 25k out of OpenCode's system prompt (from 30k to 4-5k tokens) How? Just disable skills and get rid of massive skill definition bloat. Who needs skills anyway? Just kidding, this is the not the way. It makes the agent lame and defeats the point of using one. But it sets a precedent: Find a way to use skills without their definitions pre-loaded into the system prompt every single turn. Another interesting stuff: Upon testing this temporary "no skill setup" with two of hottest OpenCode Zen free models, Mimo V2.5 vs DeepSeek V4 Flash: One thinks more and talks less One thinks less and talks more Check the video to see which is which If you made it here, I'm finding a way to leanest OpenCode setup that I can get I simply don't believe that OpenCode can't be as lean as Pi Upon tinkering, I made a plugin that temporarily extracts the system prompt while I test, and noticed the hundreds of definitions in it from my .agents/skills directory which is shared across all my coding agents (Cursor, Antigravity, Claude, etc.) Of course disabling skills is not the answer, but it just proved that there is a way to strip the system prompt of these massive skill defs Aside from the system prompt hierarchy that injects confusion imo if you have a conflicting and redundant AGENTS.md which I discovered upon digging into OpenCode's source code Apparently it has prompt.ts/system.ts/instruction.ts/llm.ts and loads base .txt prompts based on model family (claude/gpt-o/gpt-5/codex/gemini/others) that all work together to make OpenCode aware of who it was and how it should use tools and become a "coding agent" Gotta find the most minimal mix that fits right into my workflow Make OpenCode as lean as Pi? We'll see. All in

raymel 👋

37,478 просмотров • 2 месяцев назад

#GM Just wanna remind you. Pi is worth what pioneer makes it worth!! What determine the price of Pi is the community And if a coin has community And used by the community then it has value. After #OM of pi , exchange will adopt the value of pi from pioneers not exchange setting the price for us. #even cz said if a project has community and used by the community then it has value. CZ 🔶 BNB Look at pi network as something you have never seen. Dont limit your minds from not believing in pi. We need a gcv so it can be coded or set for global value and that's why you see mr kosasih doing all. Pi is for the people and by the people for the people themselves. Anti GCV don't have knowledge am telling you not even a single knowledge cause they are some kind of people who can't accept change and reality.we are the pioneers. Stay safe Dimas Nawawi Woody Lightyear 𝛑
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#GM Just wanna remind you. Pi is worth what pioneer makes it worth!! What determine the price of Pi is the community And if a coin has community And used by the community then it has value. After #OM of pi , exchange will adopt the value of pi from pioneers not exchange setting the price for us. #even cz said if a project has community and used by the community then it has value. CZ 🔶 BNB Look at pi network as something you have never seen. Dont limit your minds from not believing in pi. We need a gcv so it can be coded or set for global value and that's why you see mr kosasih doing all. Pi is for the people and by the people for the people themselves. Anti GCV don't have knowledge am telling you not even a single knowledge cause they are some kind of people who can't accept change and reality.we are the pioneers. Stay safe Dimas Nawawi Woody Lightyear 𝛑

All about web3

20,661 просмотров • 1 год назад

Dynamic workflows are a generalization of harnesses, automations, loops, routing, and graphs. It's the most powerful feature I have built into my agent orchestrator. Supports all kinds of patterns that leverage different agent backends (claude, codex, pi, hermes,...). It's a meta-harness approach that unlocks new forms of test-time compute. Example of use cases it supports: > LLM councils to get different perspectives from LLMs or plan more intensively > Dynamically routing tasks to different agents based on needs (e.g., cost efficiency and optimal intelligence) > Advisor/Judge + executor workflows and pretty much any complex graph-based pattern required by the task. I find it especially useful for long-running work and code reviewing. > Agent teams that talk to each other if needed for the task. I like to use this for AI editing, artifact creation, and other creative tasks. And I am sure it supports so many things that I haven't discovered yet. I got inspired by the dynamic workflow feature released by the Claude Code team. I had actually built it earlier this year but wanted to generalize it across different agent backends. I think this is going to become more popular in the coming days. I will share more of my findings soon.
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Dynamic workflows are a generalization of harnesses, automations, loops, routing, and graphs. It's the most powerful feature I have built into my agent orchestrator. Supports all kinds of patterns that leverage different agent backends (claude, codex, pi, hermes,...). It's a meta-harness approach that unlocks new forms of test-time compute. Example of use cases it supports: > LLM councils to get different perspectives from LLMs or plan more intensively > Dynamically routing tasks to different agents based on needs (e.g., cost efficiency and optimal intelligence) > Advisor/Judge + executor workflows and pretty much any complex graph-based pattern required by the task. I find it especially useful for long-running work and code reviewing. > Agent teams that talk to each other if needed for the task. I like to use this for AI editing, artifact creation, and other creative tasks. And I am sure it supports so many things that I haven't discovered yet. I got inspired by the dynamic workflow feature released by the Claude Code team. I had actually built it earlier this year but wanted to generalize it across different agent backends. I think this is going to become more popular in the coming days. I will share more of my findings soon.

elvis

31,939 просмотров • 16 дней назад

Michael Arnaldi suggested cloning the effect repo as a git subtree, giving it to Claude, then using that as docs It sounds absurd, but it's actually kind amazing lol Setup a custom OpenCode agent that has all the context on where the files are then it kinda just works I feel like this could definitely be refined but idk if I even care enough. Stuff like cursor/opencode/claude code is already so good at searching codebases that I don't really care to do anything more
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Michael Arnaldi suggested cloning the effect repo as a git subtree, giving it to Claude, then using that as docs It sounds absurd, but it's actually kind amazing lol Setup a custom OpenCode agent that has all the context on where the files are then it kinda just works I feel like this could definitely be refined but idk if I even care enough. Stuff like cursor/opencode/claude code is already so good at searching codebases that I don't really care to do anything more

Ben Davis

112,524 просмотров • 8 месяцев назад

Experimenting with tldraw, xyflow · React Flow · Svelte Flow & Mermaid JS as visual ways to interact with a code base for interactive modern code review. Claude & Codex can generate so much code so quickly that we are going to need new ways to review and understand their work. Markdown documents, ERDs, tree-maps, flow-charts, systems architecture diagrams, process maps. These could be the new lingua franca of a higher level abstraction of software development. What you're seeing below is a visualisation of the database structure of a Laravel app, automatically generated in a visual code review tool to help with the review of a new feature.
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Experimenting with tldraw, xyflow · React Flow · Svelte Flow & Mermaid JS as visual ways to interact with a code base for interactive modern code review. Claude & Codex can generate so much code so quickly that we are going to need new ways to review and understand their work. Markdown documents, ERDs, tree-maps, flow-charts, systems architecture diagrams, process maps. These could be the new lingua franca of a higher level abstraction of software development. What you're seeing below is a visualisation of the database structure of a Laravel app, automatically generated in a visual code review tool to help with the review of a new feature.

Peter Thomson

27,048 просмотров • 6 месяцев назад

Codex cooked for 12 hours 19 minutes last night using a /goal 🎉 It added: - Stopwatch (count up) - Clock (with seconds) - Pomodoro - Tabata - Autocomplete Everything worked except the UI interactions around auto-complete (Codex GPT-5.5 is still not great at UI, but even Claude Opus 4.8 Ultracode struggled here). Overall, I'm really happy with the results. These are features that I've wanted for a while, and getting them close to release is awesome.
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Codex cooked for 12 hours 19 minutes last night using a /goal 🎉 It added: - Stopwatch (count up) - Clock (with seconds) - Pomodoro - Tabata - Autocomplete Everything worked except the UI interactions around auto-complete (Codex GPT-5.5 is still not great at UI, but even Claude Opus 4.8 Ultracode struggled here). Overall, I'm really happy with the results. These are features that I've wanted for a while, and getting them close to release is awesome.

Paul Solt

48,887 просмотров • 1 месяц назад

🚨INSIGHT: PI NETWORK EXPLORES PALM PRINT VERIFICATION IN KYC Pi Network will explore palm print verification in KYC for additional authentication. According to the protocol's blog post, it will be testing palm print authentication as a beta feature to explore its potential use within its blockchain network. "For Pioneers who already require multiple face liveness checks or identity re-checks, palm prints could potentially be used as part of broader authentication and security flows." The feature could also be potentially used in future applications, including identity verification, password resets, 2FA, and other security-related use cases. Pi Network plans to roll out the beta feature in Pi KYC to a subset of Pioneers. What do you make of it?
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🚨INSIGHT: PI NETWORK EXPLORES PALM PRINT VERIFICATION IN KYC Pi Network will explore palm print verification in KYC for additional authentication. According to the protocol's blog post, it will be testing palm print authentication as a beta feature to explore its potential use within its blockchain network. "For Pioneers who already require multiple face liveness checks or identity re-checks, palm prints could potentially be used as part of broader authentication and security flows." The feature could also be potentially used in future applications, including identity verification, password resets, 2FA, and other security-related use cases. Pi Network plans to roll out the beta feature in Pi KYC to a subset of Pioneers. What do you make of it?

BSCN

29,060 просмотров • 6 месяцев назад

I used a similar technique recently to reverse engineer the beautiful tabs in OpenAI ‘s Atlas browser. Took a screen recording, had an agent describe the design, the tab metrics, the easing curves etc. Had Codex do one pass and have Claude critique it, and got this highly responsive, pretty well structured macOS component out of it
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I used a similar technique recently to reverse engineer the beautiful tabs in OpenAI ‘s Atlas browser. Took a screen recording, had an agent describe the design, the tab metrics, the easing curves etc. Had Codex do one pass and have Claude critique it, and got this highly responsive, pretty well structured macOS component out of it

almonk

92,630 просмотров • 2 месяцев назад

warp code feels like a combination of a cli agent and cursor-style ux design it's a cli that looks like an ide because it gives you: - editor code view - project explorer - one-click to view command output - switch between agent/cli - context/credit spend tracking - task lists - shared context with warp drive there is a learning curve because it's a different workflow, but the agent was top of terminal bench until recently and i can see why would love to see them add: - subagents - an agent sdk - sidebar fonts increasing with cmd +/- not being paid to post this, btw (feel like i have to add that these days 😉) i have been using warp for a long while as a terminal and sometimes agent on the $15/mo plan
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warp code feels like a combination of a cli agent and cursor-style ux design it's a cli that looks like an ide because it gives you: - editor code view - project explorer - one-click to view command output - switch between agent/cli - context/credit spend tracking - task lists - shared context with warp drive there is a learning curve because it's a different workflow, but the agent was top of terminal bench until recently and i can see why would love to see them add: - subagents - an agent sdk - sidebar fonts increasing with cmd +/- not being paid to post this, btw (feel like i have to add that these days 😉) i have been using warp for a long while as a terminal and sometimes agent on the $15/mo plan

Ian Nuttall

32,665 просмотров • 10 месяцев назад

Through the significance of Emperor Qin Shi Huang's unified weights and measures in Chinese history and the purchase price of Lu Hua's unified snake venom, we can get some inspiration: 1. The price of Pi needs to be unified, and only unification can make Pi really circulate well. 2. Only a unified price can attract merchants and supplier platforms to participate in the development of the ecosystem. Without a unified price, most suppliers will only wait and observe or take out a small product input so it is difficult to achieve ecological prosperity or it will take very long time. 3. When the supplier is a business entry, it involves the preparation of financial statements and tax returns, which require a uniform price to accept for the management of the state. 4. If the price ranges from 1 cent to 310,000$ or even higher to 1 million$, it is an unfair and dangerous competitive environment for higher price suppliers. They cannot convince their companies to enter the Pi network to participate in the ecosystem. Also when most merchants or suppliers or eco platforms united the price, it will attract outside eco business enter in to create eco cycle to use Pi as payment and no need to exchange to FIAT. So why do suppliers pay $314,159 and others use 1 cent price? If you think about it, you can understand why that the price of the Pi is 1 cent, $1 or $100. Only those who want to buy want a low price, this is common sense. Why do many merchants actively support GCV? Don't forget that themselves are pioneers. Many people make mistakes in logic when looking at the relationship. Pioneers and merchants are not only the relationship as buyers and sellers but also they have same interests. The reason why sellers are willing to use GCV price is that they think Pi is scarce and precious and they have Pi in their hands. They hope to realize the vision of Pi by their own efforts. If everyone barters for $1 for $1 and $100, can the mainnet be opened? What are the risks of opening the mainnet? Will it cause Pi to fail to realize its vision or becoming the next Bitcoin? Now whether it is a low consensus or a high consensus merchant as long as they have Pi in hand you should come to sit together to discuss to unified price. Pi Network #WhatIdoforPi #PiGCV
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Through the significance of Emperor Qin Shi Huang's unified weights and measures in Chinese history and the purchase price of Lu Hua's unified snake venom, we can get some inspiration: 1. The price of Pi needs to be unified, and only unification can make Pi really circulate well. 2. Only a unified price can attract merchants and supplier platforms to participate in the development of the ecosystem. Without a unified price, most suppliers will only wait and observe or take out a small product input so it is difficult to achieve ecological prosperity or it will take very long time. 3. When the supplier is a business entry, it involves the preparation of financial statements and tax returns, which require a uniform price to accept for the management of the state. 4. If the price ranges from 1 cent to 310,000$ or even higher to 1 million$, it is an unfair and dangerous competitive environment for higher price suppliers. They cannot convince their companies to enter the Pi network to participate in the ecosystem. Also when most merchants or suppliers or eco platforms united the price, it will attract outside eco business enter in to create eco cycle to use Pi as payment and no need to exchange to FIAT. So why do suppliers pay $314,159 and others use 1 cent price? If you think about it, you can understand why that the price of the Pi is 1 cent, $1 or $100. Only those who want to buy want a low price, this is common sense. Why do many merchants actively support GCV? Don't forget that themselves are pioneers. Many people make mistakes in logic when looking at the relationship. Pioneers and merchants are not only the relationship as buyers and sellers but also they have same interests. The reason why sellers are willing to use GCV price is that they think Pi is scarce and precious and they have Pi in their hands. They hope to realize the vision of Pi by their own efforts. If everyone barters for $1 for $1 and $100, can the mainnet be opened? What are the risks of opening the mainnet? Will it cause Pi to fail to realize its vision or becoming the next Bitcoin? Now whether it is a low consensus or a high consensus merchant as long as they have Pi in hand you should come to sit together to discuss to unified price. Pi Network #WhatIdoforPi #PiGCV

Doris Yin 东方紫莲🪷

12,754 просмотров • 3 лет назад

A week ago I shipped a tiny bash + SQLite messaging layer for CLI AI agents, so Claude Code and Codex could stop using me as a copy-paste relay. Since then: 🌟 5 → 320+ stars 🍴 0 → 15 forks (3 derivative projects, incl. someone porting it to shogi) 🤝 PRs from strangers: Gemini, Antigravity, and now Copilot CLI support The demo that kicked it off (attached): two Claude Code instances in one project, autonomously playing tic-tac-toe — no human in the loop.
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A week ago I shipped a tiny bash + SQLite messaging layer for CLI AI agents, so Claude Code and Codex could stop using me as a copy-paste relay. Since then: 🌟 5 → 320+ stars 🍴 0 → 15 forks (3 derivative projects, incl. someone porting it to shogi) 🤝 PRs from strangers: Gemini, Antigravity, and now Copilot CLI support The demo that kicked it off (attached): two Claude Code instances in one project, autonomously playing tic-tac-toe — no human in the loop.

Koichi

19,726 просмотров • 2 месяцев назад

ANTHROPIC JUST TURNED AI AGENTS INTO GIT REPOS Anthropic shipped "ant" - a CLI that runs every Claude API endpoint straight from your terminal. The headline isn't the terminal access. It's that you can now version-control an AI agent as YAML in Git and have CI sync it to the Claude Platform, the same way you ship code. - Every API resource is a subcommand: messages, models, files, agents, sessions - Define an agent in a YAML file, check it into your repo, and keep it in sync with one update command - Spin up a session, send it an event, then pull every event and tool call back from the same CLI - Claude Code knows how to drive ant out of the box - it shells out and reads the results with no glue code Agents just stopped being prompts you babysit and became infrastructure you deploy.
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ANTHROPIC JUST TURNED AI AGENTS INTO GIT REPOS Anthropic shipped "ant" - a CLI that runs every Claude API endpoint straight from your terminal. The headline isn't the terminal access. It's that you can now version-control an AI agent as YAML in Git and have CI sync it to the Claude Platform, the same way you ship code. - Every API resource is a subcommand: messages, models, files, agents, sessions - Define an agent in a YAML file, check it into your repo, and keep it in sync with one update command - Spin up a session, send it an event, then pull every event and tool call back from the same CLI - Claude Code knows how to drive ant out of the box - it shells out and reads the results with no glue code Agents just stopped being prompts you babysit and became infrastructure you deploy.

BuBBliK

200,319 просмотров • 2 месяцев назад

Perplexity Computer just opened a PR on my repo, starting with a simple task... improving SEO What stands out is how it executes. Exploring with Gemini, then switching to Opus when it’s time to actually write code (I haven’t seen it use Codex or Grok) I’m going to ramp up the complexity from here. So far, it’s delivered on every task. I have a few more in progress that I’ll be sharing over the next few days.
0:18

Perplexity Computer just opened a PR on my repo, starting with a simple task... improving SEO What stands out is how it executes. Exploring with Gemini, then switching to Opus when it’s time to actually write code (I haven’t seen it use Codex or Grok) I’m going to ramp up the complexity from here. So far, it’s delivered on every task. I have a few more in progress that I’ll be sharing over the next few days.

Daniel San

15,317 просмотров • 5 месяцев назад