Загрузка видео...

Не удалось загрузить видео

На главную

I built an app that runs Claude Code, Codex, Cursor, Grok, Antigravity, OpenCode, and Pi side by side in my Mac notch. Agent finishes → notch pops. Needs approval → notch pops. One click back to that exact session. no more switching between apps.

edwardluox's profile picture

Edward Luo

1,755 subscribers

924,237 просмотров • 1 месяц назад •via X (Twitter)

Наука и технологии
LIVE

Anya Rossi• Live Now

Private livecam show

Комментарии: 0

Нет доступных комментариев

Здесь появятся комментарии из оригинального поста

Похожие видео

New in Orca: search agent sessions by keyword and resume them instantly ⚡️ Ever lose track of which agent session had that one important change? Not anymore. Search → find the session → jump right back in. Works with Claude Code, Codex, OpenCode, Pi, etc
0:12

New in Orca: search agent sessions by keyword and resume them instantly ⚡️ Ever lose track of which agent session had that one important change? Not anymore. Search → find the session → jump right back in. Works with Claude Code, Codex, OpenCode, Pi, etc

Orca ADE

11,809 просмотров • 2 месяцев назад

GPT-5.5 in Codex is built for long-session agent work. But context still doesn't follow you across projects, agents, or teammates. ByteRover does that + Save you tokens -> No rewriting context when you switch from Claude Code to Codex. Now connecting Codex, Claude Code, OpenClaw, Hermes, and 22+ more agents. Your context moves with you. → personal context for solo work → team context for shared decisions and bug history
0:17

GPT-5.5 in Codex is built for long-session agent work. But context still doesn't follow you across projects, agents, or teammates. ByteRover does that + Save you tokens -> No rewriting context when you switch from Claude Code to Codex. Now connecting Codex, Claude Code, OpenClaw, Hermes, and 22+ more agents. Your context moves with you. → personal context for solo work → team context for shared decisions and bug history

andy nguyen

12,437 просмотров • 4 месяцев 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 🙂
0:18

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

536,970 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
0:11

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 👋

37,939 просмотров • 3 месяцев 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.
0:11

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

32,623 просмотров • 1 месяц назад

We (Claude and I) made a new package: voxmlx It's an MLX implementation of Mistral's Voxtral mini realtime speech recognition model. It supports streaming audio and runs pretty fast on a laptop. To use it, simply: `uvx voxmlx` Also I did not write a single line of code for this package. Every line of code was written by Claude Code. More on that in thread.
0:16

We (Claude and I) made a new package: voxmlx It's an MLX implementation of Mistral's Voxtral mini realtime speech recognition model. It supports streaming audio and runs pretty fast on a laptop. To use it, simply: `uvx voxmlx` Also I did not write a single line of code for this package. Every line of code was written by Claude Code. More on that in thread.

Awni Hannun

33,896 просмотров • 6 месяцев назад

MARCUS CHEN STACKED 30 MAC MINIS INTO AN AI SERVER FARM. ONE $599 MAC MINI REPLACES YOUR $200/MONTH CLAUDE CODE BILL WITH $3 IN ELECTRICITY two months ago a developer posted his claude code bill on reddit. $170 in 10 days. someone replied "i bought a mac mini m4. haven't paid anthropic since." apple stores ran out of mac minis the same week the m4 chip has 120 gb/s memory bandwidth and unified memory architecture. cpu and gpu share one pool so the model loads once and both read from it. a $599 mac mini runs ai faster than a $1,500 windows pc with a discrete gpu since january 2026 ollama supports the anthropic messages api format. claude code connects directly to your local mac mini with one environment variable. same interface, zero api costs, $0 per request a heavy developer pays $459 a month across claude code max, chatgpt pro, gemini, cursor and copilot. that's $5,508 a year. the mac mini pays off in 3 months and runs on $3 in electricity after that uber rolled out claude code to 5,000 engineers and burned through their $3.4 billion 2026 ai budget in 4 months. the people who own the hardware in 2026 are going to look very far ahead in 2028 bookmark this and read the article below
0:16

MARCUS CHEN STACKED 30 MAC MINIS INTO AN AI SERVER FARM. ONE $599 MAC MINI REPLACES YOUR $200/MONTH CLAUDE CODE BILL WITH $3 IN ELECTRICITY two months ago a developer posted his claude code bill on reddit. $170 in 10 days. someone replied "i bought a mac mini m4. haven't paid anthropic since." apple stores ran out of mac minis the same week the m4 chip has 120 gb/s memory bandwidth and unified memory architecture. cpu and gpu share one pool so the model loads once and both read from it. a $599 mac mini runs ai faster than a $1,500 windows pc with a discrete gpu since january 2026 ollama supports the anthropic messages api format. claude code connects directly to your local mac mini with one environment variable. same interface, zero api costs, $0 per request a heavy developer pays $459 a month across claude code max, chatgpt pro, gemini, cursor and copilot. that's $5,508 a year. the mac mini pays off in 3 months and runs on $3 in electricity after that uber rolled out claude code to 5,000 engineers and burned through their $3.4 billion 2026 ai budget in 4 months. the people who own the hardware in 2026 are going to look very far ahead in 2028 bookmark this and read the article below

starmex

357,679 просмотров • 3 месяцев назад

19-year-old from china makes $9,000/month designing product sites and ships each one in an afternoon. here's his exact setup the whole thing runs on two tools that each do one job: > brief written by hand: 5 min > Moonchild builds the design system, then every screen from it: 20 min > MCP hands the design to Claude as real structure, not a screenshot: instant > Claude Code reads those exact tokens and builds the live app: 20 min > second Claude session reviews the build for drift: 10 min total: about an hour. screen five still matches screen one. no agency, no dev, no design team the trick is MCP. the design tool passes Claude the actual colors, components and layout, so it builds from the source instead of guessing from a picture. full pipeline, every prompt, in the article above.
0:12

19-year-old from china makes $9,000/month designing product sites and ships each one in an afternoon. here's his exact setup the whole thing runs on two tools that each do one job: > brief written by hand: 5 min > Moonchild builds the design system, then every screen from it: 20 min > MCP hands the design to Claude as real structure, not a screenshot: instant > Claude Code reads those exact tokens and builds the live app: 20 min > second Claude session reviews the build for drift: 10 min total: about an hour. screen five still matches screen one. no agency, no dev, no design team the trick is MCP. the design tool passes Claude the actual colors, components and layout, so it builds from the source instead of guessing from a picture. full pipeline, every prompt, in the article above.

Ridark

19,477 просмотров • 2 месяцев назад

▣ Introducing Endless: infinite inference (kinda). An experimental harness to milk every ounce out of your Codex subscription. Since Codex can let an in-progress turn keep going even after your usage hits 100%, why not put that to the test? Endless starts one Codex turn and gives the agent a wait_for_user_input tool. Once it finishes a task, it calls that tool and waits. Your next message becomes the tool result, keeping the entire session inside the same turn. It runs through Codex’s own app server using your existing ChatGPT login. Native tools, automatic compaction, context tracking, and quota tracking still work as usual. ⚠️ NOTE: I CAN’T CONFIRM THAT YOU WON’T GET BANNED OR PUNISHED FOR USING THIS TOOL. USE IT AT YOUR OWN RISK.
0:18

▣ Introducing Endless: infinite inference (kinda). An experimental harness to milk every ounce out of your Codex subscription. Since Codex can let an in-progress turn keep going even after your usage hits 100%, why not put that to the test? Endless starts one Codex turn and gives the agent a wait_for_user_input tool. Once it finishes a task, it calls that tool and waits. Your next message becomes the tool result, keeping the entire session inside the same turn. It runs through Codex’s own app server using your existing ChatGPT login. Native tools, automatic compaction, context tracking, and quota tracking still work as usual. ⚠️ NOTE: I CAN’T CONFIRM THAT YOU WON’T GET BANNED OR PUNISHED FOR USING THIS TOOL. USE IT AT YOUR OWN RISK.

maria

254,287 просмотров • 15 дней назад

I built an ios app that lets you setup an open claw agent from your phone in less than 30 seconds. My mom has an open claw assistant now. No api keys, no vps, no setup, no mac mini. You just log in and its spins up your own ai agent. Most people don't understand how open claw is different from chat gpt. I am building one tap skills so that anyone can outsource their work and organize their life. People spend $2500 a month on tokens. I am adding cost efficient models with one tap switching so you don't waste your money. Most of these simple setup claw projects are completely unsafe, I have passed apple review and am working with world class security professionals to keep your data safe.
0:10

I built an ios app that lets you setup an open claw agent from your phone in less than 30 seconds. My mom has an open claw assistant now. No api keys, no vps, no setup, no mac mini. You just log in and its spins up your own ai agent. Most people don't understand how open claw is different from chat gpt. I am building one tap skills so that anyone can outsource their work and organize their life. People spend $2500 a month on tokens. I am adding cost efficient models with one tap switching so you don't waste your money. Most of these simple setup claw projects are completely unsafe, I have passed apple review and am working with world class security professionals to keep your data safe.

Max Blade

26,095 просмотров • 6 месяцев назад

I’ve built a background daemon that connects to Linear for one of my enterprise clients (multi-billion company). It runs autonomous AI workflows: – Creates PRDs from tickets – Waits for human review – Implements, verifies, and opens PRs automatically Built with LangGraph for orchestration, Codex + Claude for deep code understanding, direct LLM's API calls (via OpenRouter) for more deterministic tasks. It’s pretty cool watching the whole flow execute live in the console ⚡️
0:18

I’ve built a background daemon that connects to Linear for one of my enterprise clients (multi-billion company). It runs autonomous AI workflows: – Creates PRDs from tickets – Waits for human review – Implements, verifies, and opens PRs automatically Built with LangGraph for orchestration, Codex + Claude for deep code understanding, direct LLM's API calls (via OpenRouter) for more deterministic tasks. It’s pretty cool watching the whole flow execute live in the console ⚡️

Krzysztof Zabłocki

17,019 просмотров • 10 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.
0:18

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

200,456 просмотров • 3 месяцев назад

‼️found a site that ends AI design slop. superrr is an MCP server that gives your coding agent taste. they measured 132 real landing pages, verified 123 of them and pulled out 17 design directions with exact tokens. the agents still writes the code. superrr picks the direction, hands it the structure then grades what it built by scanning the live page after. no more generic purple gradient landing pages. their landing page was one-shotted with it. three lines to connect to Claude. link:
0:13

‼️found a site that ends AI design slop. superrr is an MCP server that gives your coding agent taste. they measured 132 real landing pages, verified 123 of them and pulled out 17 design directions with exact tokens. the agents still writes the code. superrr picks the direction, hands it the structure then grades what it built by scanning the live page after. no more generic purple gradient landing pages. their landing page was one-shotted with it. three lines to connect to Claude. link:

sui

25,411 просмотров • 24 дней назад

we just released a new blog "Training a coding agent using the OpenCode harness in remote HF sandboxes with TRL and OpenEnv" you can take a real coding agent (OpenCode), let it run its own tool loop against real coding problems, and train it with RL on the exact tokens it produced and every rollout runs in its own remote HF sandbox, so rollouts scale out beyond one machine the loop: - OpenCode owns its tool loop inside an OpenEnv sandbox - an in-sandbox proxy records the real token ids + logprobs, per turn - a hidden-test verifier scores the result, and that is the reward - TRL trains with AsyncGRPO, weights sync back to vLLM over NCCL blog + runnable example:
0:13

we just released a new blog "Training a coding agent using the OpenCode harness in remote HF sandboxes with TRL and OpenEnv" you can take a real coding agent (OpenCode), let it run its own tool loop against real coding problems, and train it with RL on the exact tokens it produced and every rollout runs in its own remote HF sandbox, so rollouts scale out beyond one machine the loop: - OpenCode owns its tool loop inside an OpenEnv sandbox - an in-sandbox proxy records the real token ids + logprobs, per turn - a hidden-test verifier scores the result, and that is the reward - TRL trains with AsyncGRPO, weights sync back to vLLM over NCCL blog + runnable example:

Sergio Paniego

37,936 просмотров • 1 месяц назад

I just built a Claude Code skill that scores whether your landing page actually keeps your Meta ad's promise 🤯 Drop in your ad and the page it points to. It reads both, scores the "ad scent" from click to page, and finds the exact line where the page breaks the promise that won the click. All inside Claude Code. Perfect for DTC brands and media buyers who pour everything into the ad and the CPA but never grade the seam in between. If you're scaling spend on a winning ad, the click is landing on a page that opens with something slightly different, the ad promised 50% off and the page shows full price, the ad hooked "for oily skin" and the page is a generic homepage, and nothing looks broken, but the visitor feels it and bounces... That gap has a name in conversion work: message match. And you already paid for the click you're losing. Here's what it does: → Drop in your ad (headline, copy, offer, CTA) and the landing-page URL → It fetches the live page and reads what's actually above the fold → Grades 7 continuity dimensions: promise, offer, angle, CTA, audience, proof, visual → Shows your ad's words next to your page's words, so every gap is right there → Rewrites your hero headline so the page keeps the ad's promise → Renders a dashboard with a Match Score out of 100 No guessing why the click bounced. No blaming the creative for a page problem. No buying more traffic to fix a copy problem. What you get: → A Match Score on every ad-to-page pair before you scale → The ad-side vs page-side quotes, side by side, for every leak → A hero rewrite you can paste straight onto the page → A dashboard you can hand to your team or client I'm giving away the full skill completely for free. Built 100% in Claude Code. No API keys. Want the skill? > Like this post > Comment "MATCH" And I'll send it over (must be following so I can DM)
0:14

I just built a Claude Code skill that scores whether your landing page actually keeps your Meta ad's promise 🤯 Drop in your ad and the page it points to. It reads both, scores the "ad scent" from click to page, and finds the exact line where the page breaks the promise that won the click. All inside Claude Code. Perfect for DTC brands and media buyers who pour everything into the ad and the CPA but never grade the seam in between. If you're scaling spend on a winning ad, the click is landing on a page that opens with something slightly different, the ad promised 50% off and the page shows full price, the ad hooked "for oily skin" and the page is a generic homepage, and nothing looks broken, but the visitor feels it and bounces... That gap has a name in conversion work: message match. And you already paid for the click you're losing. Here's what it does: → Drop in your ad (headline, copy, offer, CTA) and the landing-page URL → It fetches the live page and reads what's actually above the fold → Grades 7 continuity dimensions: promise, offer, angle, CTA, audience, proof, visual → Shows your ad's words next to your page's words, so every gap is right there → Rewrites your hero headline so the page keeps the ad's promise → Renders a dashboard with a Match Score out of 100 No guessing why the click bounced. No blaming the creative for a page problem. No buying more traffic to fix a copy problem. What you get: → A Match Score on every ad-to-page pair before you scale → The ad-side vs page-side quotes, side by side, for every leak → A hero rewrite you can paste straight onto the page → A dashboard you can hand to your team or client I'm giving away the full skill completely for free. Built 100% in Claude Code. No API keys. Want the skill? > Like this post > Comment "MATCH" And I'll send it over (must be following so I can DM)

Mike Futia

10,787 просмотров • 1 месяц назад

I built a 1-click deploy for Hermes Agent No terminal, no Docker, no API keys. In one click it: → Spins up a dedicated cloud container → Configures Hermes with persistent memory & 70+ skills → Connects it to your Telegram bot → Goes live in under 60 seconds Your own AI agent that learns, creates skills, and gets smarter the longer it runs. Reply "HERMES" + RT and I'll send you the link (must be following so I can DM)
0:16

I built a 1-click deploy for Hermes Agent No terminal, no Docker, no API keys. In one click it: → Spins up a dedicated cloud container → Configures Hermes with persistent memory & 70+ skills → Connects it to your Telegram bot → Goes live in under 60 seconds Your own AI agent that learns, creates skills, and gets smarter the longer it runs. Reply "HERMES" + RT and I'll send you the link (must be following so I can DM)

Chris

34,698 просмотров • 5 месяцев 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.
0:13

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

19,766 просмотров • 3 месяцев назад

Claude Mobile starts the idea... Ghostty finishes it I basically use Claude Mobile as a notepad now. Whenever something comes to mind, I open the app, pick a repo, and ask Claude to start exploring. Then I just let it run while I go on with my day. Later I jump into Claude Desktop and I’m right back in the same session, with context, structure, and a clearer shape of the idea. I tweak a few things to set up the coding phase. Finally, one click to Ghostty (video), open a couple of worktrees, and start working on the PR. IMPORTANT: when you move to Ghostty, it must be the exact same repo you started on mobile, otherwise the --teleport command will fail
0:15

Claude Mobile starts the idea... Ghostty finishes it I basically use Claude Mobile as a notepad now. Whenever something comes to mind, I open the app, pick a repo, and ask Claude to start exploring. Then I just let it run while I go on with my day. Later I jump into Claude Desktop and I’m right back in the same session, with context, structure, and a clearer shape of the idea. I tweak a few things to set up the coding phase. Finally, one click to Ghostty (video), open a couple of worktrees, and start working on the PR. IMPORTANT: when you move to Ghostty, it must be the exact same repo you started on mobile, otherwise the --teleport command will fail

Daniel San

67,891 просмотров • 7 месяцев назад

$35 OF FREE CLAUDE OPUS 5 CREDITS FOR A WEEK, NO CARD ANYWHERE • the credit > Sign up with Google and the trial activates on its own, nothing to claim manually: > Opus 5 sits alongside Opus 4.8, Sonnet 4.6 and Haiku on the same key. > The window runs a week from activation. • wiring it up > base url: > model id: claude-opus-5 > In OpenCode Desktop hit Ctrl+, and add a custom provider with the id aerolink. > The same key drops into Codex, Cursor and Claude Code with nothing else changed. One key, not locked to one client -> every tool that takes a custom OpenAI-compatible endpoint reads it the same way. It routes through a third-party proxy rather than an official Anthropic channel, so keep client work off it ↓
0:16

$35 OF FREE CLAUDE OPUS 5 CREDITS FOR A WEEK, NO CARD ANYWHERE • the credit > Sign up with Google and the trial activates on its own, nothing to claim manually: > Opus 5 sits alongside Opus 4.8, Sonnet 4.6 and Haiku on the same key. > The window runs a week from activation. • wiring it up > base url: > model id: claude-opus-5 > In OpenCode Desktop hit Ctrl+, and add a custom provider with the id aerolink. > The same key drops into Codex, Cursor and Claude Code with nothing else changed. One key, not locked to one client -> every tool that takes a custom OpenAI-compatible endpoint reads it the same way. It routes through a third-party proxy rather than an official Anthropic channel, so keep client work off it ↓

slash1s

20,727 просмотров • 20 дней 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
0:18

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