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.show more

my Mac notch now tracks every AI usage limit... I have. Claude Max, Codex Pro, Cursor, Grok, Kimi, Antigravity. Fable's weekly limit → alongside the usual 5h / 7d. Codex reset cards → how many left, when the next expires. no more surprise rate limits.show more

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, etcshow more

You can now run Grok inside Claude Code and... Codex, using your existing subscription. it's called grok-plugin. Grok’s genuinely good right now, but if your setup lives in Claude Code and Codex, switching to use it is a pain. this solves that exact issue: > Grok in Claude Code and Codex > directly auths through X Premium or Supergrok, no api key > your workflow and subagents stay untouched free and open source. the low-friction way to test Grok in the tools you already use.show more

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 historyshow more

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 🙂show more

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 inshow more

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.show more

Stop manually making flowcharts. Try this GitHub skill with... Claude Code. I found an open-source tool that turns a plain description of a software system into a clean, interactive diagram. It's called Archify, and it has more than 66,000 stars on GitHub. You add it as a skill to an AI coding agent like Claude Code, Codex, Cursor, or OpenCode. Then you describe the system in the chat in one line. Archify turns that line into a single HTML file you can open, click through, and send to anyone. If you point your agent at an existing codebase, it reads the code and Archify maps how the pieces connect. I liked five things about it. 1. It makes five kinds of diagrams, including system maps and step-by-step workflows. 2. You can click any piece and trace what connects to it. 3. It checks the layout before it hands the diagram over, so arrows don't pile up and labels don't overlap. 4. It has dark and light themes and exports to PNG, SVG, or a short video. 5. You keep editing in plain chat, with requests like "add Redis" or "highlight the rollback path." You don't need a codebase to use it. A description in the chat is enough.show more

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.show more

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 belowshow more

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.show more

▣ 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.show more

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.show more

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 ⚡️show more

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.show more

Own your personal agent, folks. Just built my own... little personal agent with Pi's Pi Durable. I wanted to see how quickly I could build an OpenAI dots clone with open-source tools. I am amazed at how quickly I got this off the ground. It's proactive. It keeps working when you're not watching. It remembers you, runs jobs on a schedule, waits for your approval, and uses its own computer. Pi Durable makes that possible. Every step is checkpointed. I can kill the process mid-task, and My Pi picks up right where it left off. Memory lives in durable documents. What My Pi learns about me in one Space survives a crash and carries over to every other Space. Approvals are durable too. It also has its own computer. Each Space gets a full Linux desktop that My Pi controls with screenshots, mouse, and keyboard. The model runs through OpenRouter, so I can swap models without changing anything else. That's all configurable however you like it. If you've been wanting your own personal agent, now is a great time to build one. I am building this as an experimental ground where I can test new ideas and experiment deeply with proactive personal agents. But I plan to open-source it after testing it a bit and adding more interesting primitives. The goal is to make it customizable and easy to build on, so others can experiment with their own personal agent functionalities.show more

‼️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:show more

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)show more

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:show more

CLAUDE CODE SKILL THAT DESIGNS LOGOS AS PURE CODE... The constraint that forced the whole approach: Claude Code has no access to image generation So instead of faking it, one developer built a skill that writes the logo as SVG - actual XML - and renders that to a PNG The process runs in four phases: interview [ reads your repo first, asks about brand and audience only for what it can’t already see ] explore [ dispatches parallel agents that generate 3-5 distinct SVG concepts at once, shown side by side in an HTML preview with a light/dark toggle ] refine, export at 7 standard sizes from favicon to 2048px Because it’s real SVG and not a rasterized image, nothing about it degrades - same file works as a 16px favicon and a 2048px app icon, and every version is hand editable code afterward if you want to nudge one curve The creator’s own account of using it: roughly 15 rounds of generate, curate, cull, repeat - some concepts literally spelled out the product name, others went fully abstract, treating the whole thing like an evolutionary design process instead of a single lucky prompt The part worth remembering before you reach for a paid AI logo tool: this whole approach exists specifically because Claude Code can’t generate images - the constraint produced a better artifact than the workaround usually does full belowshow more