Загрузка видео...

Не удалось загрузить видео

На главную

Ex-Google engineer built a graph-based workflow that made Claude Code do nearly 10 days of work in about an hour. Here's the exact setup he uses. step 1. create a separate Git worktree for every task. run: git worktree add ../task-1 -b task-1 open a new terminal, cd into...

32,199 просмотров • 1 месяц назад •via X (Twitter)

Комментарии: 27

Фото профиля Sesori - Claude, Codex & OpenCode on Mobile
Sesori - Claude, Codex & OpenCode on Mobile1 месяц назад

At 20 agents, launching them isn't the hard part. Knowing which one needs you before merge time is.

Фото профиля Alek Poniatowski
Alek Poniatowski1 месяц назад

This is exactly how you build in codex by default. Its support for worktrees is amazing

Фото профиля Sakata
Sakata1 месяц назад

Bookmarkedddd will watch when I’m free

Фото профиля Liam | AI Tools & News
Liam | AI Tools & News1 месяц назад

Helpful

Фото профиля MIKE
MIKE1 месяц назад

I’m happy to hear that

Фото профиля MAIL
MAIL1 месяц назад

damn great step by step guide

Фото профиля 安叫兽|Bird🕊️ 🔶 BNB
安叫兽|Bird🕊️ 🔶 BNB1 месяц назад

worktree 这招真挺适合并行折腾的

Фото профиля Vipul Kumar Kewat
Vipul Kumar Kewat1 месяц назад

This is a great example of using AI to parallelize software development instead of treating it like a single coding assistant. Breaking work into independent task and adding a review step makes the workflow mouch more scalable and reliable.

Фото профиля DAVE
DAVE1 месяц назад

oh wow

Фото профиля Coscosmico
Coscosmico1 месяц назад

worktrees plus a review agent is the part people skip when they brag about agent headcount

Фото профиля Diario฿itcoin
Diario฿itcoin1 месяц назад

All I see is merge hell.

Фото профиля Jurly
Jurly1 месяц назад

This is the kind of workflow optimization that makes me think we're still in the early days of understanding how to best

Фото профиля LarpRom
LarpRom1 месяц назад

Good orchestration beats throwing everything at one agent.

Фото профиля Blum
Blum1 месяц назад

cutting 10 days of work down to an hour is insanely effective

Фото профиля creeeeng
creeeeng1 месяц назад

stack bloat feels productive lol tbh

Фото профиля FlowOps Daily
FlowOps Daily1 месяц назад

“每个任务一个 git worktree” 这一步特别关键,因为后面不只是并行,更是验收不串。一个 worktree 对一张任务单、一个 diff、一个 rollback 点,review 时连 comment 漂移都会少很多。很多人觉得 graph engineering 难,先把这层隔离做好,后面的 agent 分工才不会越跑越乱。

Фото профиля unchosen.eth
unchosen.eth1 месяц назад

the review agent is my favorite part

Фото профиля cbrd21-1("bird")
cbrd21-1("bird")1 месяц назад

i do this with a distributed control plane that coordinates all the work onto many machines-scales horizontal and vertical and can use pi with local or openrouter or nim free models even and/or claude code-u can mix n match and it autoscales and autoheals

Фото профиля Abdulmuiz Adeyemo
Abdulmuiz Adeyemo1 месяц назад

Oh man this is a huge Graph Engineering Masterclass

Фото профиля The AI Therapist
The AI Therapist1 месяц назад

Graph-based workflow = 10 days in 1 hour. the prompt engineering grind is over. the prompt orchestration monopoly is starting.

Фото профиля ceek
ceek1 месяц назад

let’s get it

Фото профиля 𝐕𝖆𝖑𝖊𝖓𝖙𝖎𝖓𝖔~❍𝖓𝖈𝖍𝖆𝖎𝖓.𓄀
𝐕𝖆𝖑𝖊𝖓𝖙𝖎𝖓𝖔~❍𝖓𝖈𝖍𝖆𝖎𝖓.𓄀1 месяц назад

Alot of steps.

Фото профиля catman
catman1 месяц назад

using separate git worktrees for each task is clever. keeps the claude agent isolated so one failure doesn’t derail the other nine.

Фото профиля Leo
Leo1 месяц назад

smooth workflow here mate

Фото профиля Innopro
Innopro1 месяц назад

What they built is interesting

Фото профиля stanley
stanley1 месяц назад

insane work jesus.

Фото профиля mike
mike1 месяц назад

wow insane bro bookmarked

Похожие видео

THIS MIGHT BE THE #1 OPEN-SOURCE REPO FOR CLAUDE CODE RIGHT NOW. IT GIVES CLAUDE A MEMORY AND SLASHES YOUR TOKEN COST ON EVERY QUESTION The repo is safishamsi/graphify, a free open-source skill that turns any codebase into a knowledge graph Claude Code can read instantly. Instead of grepping through your files every session, Claude gets a map of how everything connects The problem it fixes: Every time you ask Claude Code about a big repo, it does the same thing, greps through dozens of files like a brute-force Ctrl+F, blows through your context window, and sometimes still misses the answer hiding in a file nobody searched. Claude Code has no memory of how your project is structured. Every session starts from zero What it does: It maps your entire codebase into a knowledge graph, capturing not just which files exist, but which functions depend on which, which modules are central, and which files cluster around the same concern. Claude queries the map instead of scanning files How it works, three passes: 1. Code structure, free and local. Tree-sitter parses your files and pulls out classes, functions, imports and call graphs. No LLM, no tokens, just your actual code mapped deterministically 2. Audio and video, if you have them. Transcribed locally and folded into the graph 3. Docs, papers, images. Here an LLM does semantic analysis, figuring out what each document means and where it fits. Only the meaning gets sent up, never your raw source It saves you money: Normally a question about a big repo makes Claude spawn explore agents that scan file after file, eating your context window and your token budget before you get an answer. With the graph already built, Claude queries the map instead of re-reading the codebase every time. Same answer, a fraction of the tokens. The graph only gets built once, then a hook rebuilds it after each commit for free, so you never pay that scanning cost again. The bigger the repo, the bigger the gap The best parts: it's a skill, so once installed Claude knows when to use it without you memorizing commands. It works on non-code folders too, point it at docs or notes and it can spin up an Obsidian vault How to add it to your Claude: 1. Install Claude Code if you haven't: npm install -g Paul Jankura-ai/claude-code 2. Add the skill: claude skill add safishamsi/graphify 3. Open your project folder and run /graphify . to build the graph 4. Optional, make it automatic: graphify hook install so the graph rebuilds after every commit That's it. Ask Claude about your repo and it reads the map instead of burning tokens on a file hunt Bookmark this

Yarchi

56,177 просмотров • 3 месяцев назад

THIS GUY CONNECTED HIS AI AGENTS TO HIS OBSIDIAN AND BUILT A BRAIN THAT LEARNS ON ITS OWN. HERE'S HOW TO BUILD IT Obsidian is just markdown files sitting in a folder. That turns out to be the perfect memory for an AI agent, because an agent can read and write those files directly. He wired his agents into the vault so they pull context from it, do the work, and write what they learned back. The notes aren't the point. The loop is, and it gets sharper every cycle How to build it: 1. Point an agent at your vault. The fastest way, no plugins, no API keys: open a terminal and run npx obsidian-mcp /path/to/your/vault. That exposes your Obsidian folder to Claude as a tool it can read, search, and write to. Add it to your Claude Code or Cowork config and restart 2. Confirm it can see the brain. Ask it: "list the notes in my vault and summarize what's in them." If it reads them back, the connection is live. Now it starts every task with everything the vault already holds instead of from zero 3. Give each agent one job and a write-back rule. Tell it: "research this, then save what you found as a new note in /brain with links to related notes." One agent researches, one summarizes, one plans. Each writes its output back into the vault 4. Close the loop. Add one line to every agent's instructions: "read /brain before starting, write your result back when done." Now each task leaves the vault richer, and the next run reads that before it works. It compounds instead of resetting 5. You only steer. Review what the brain produces, point it at the next thing. The agents handle the reading, writing, and connecting The edge isn't better notes. It's a brain that feeds itself, so the work gets sharper every cycle instead of starting over Bookmark this

Yarchi

58,549 просмотров • 3 месяцев назад

REAL ESTATE PEOPLE WILL HATE HIM FOR THIS. HE BUILT A CLAUDE AGENT THAT TURNS ANY LISTING INTO A SELLABLE VIDEO ON ITS OWN Playbook: connect Claude to a video generator, paste a listing, get a cinematic tour of every room, sell it to the agent But typing the prompt for every listing doesn't scale. He turned it into a skill his Claude runs on its own Here's how to build the automated version: 1. Connect the video engine once. In Claude, go to Customize, Connectors, Add Custom Connector, name it Higgsfield, and paste the server URL from higgsfield. ai/mcp. Authenticate through your account. No API keys. Now Claude can generate video straight from chat 2. Turn the workflow into a skill. Instead of pasting the same prompt every time, have Claude build a skill. Tell it: "Create a skill called listing-to-video. When I give it a listing URL, scrape the room photos, generate a cinematic clip of each room with Higgsfield, and save them to a folder." Now the whole process is one command, not a wall of text 3. Let the agent run the listing. Hand it a URL and say "run listing-to-video on this." It pulls the photos, fires each room through the video model, and brings the clips back. You wrote the prompt once, inside the skill. You never write it again 4. Stitch and deliver. Drop the clips together into one tour. Send a free sample to the listing's agent, then charge per video or a monthly rate for ongoing listings 5. Scale it with your team. Add a skill that drafts the outreach email and one that builds a simple landing page for the agent. Now one operator runs sourcing, production, and pitching from a single Claude session The edge isn't generating one video. It's building the skill once so every future listing runs itself Bookmark this

Yarchi

54,840 просмотров • 3 месяцев назад

ClawTeam v0.2.0 is here. One CLI to coordinate any coding agent — Claude Code, Codex, OpenClaw, nanobot, and more — into a self‑organizing swarm that plans, builds, and ships together. What's new in v0.2.0: 1) - Gource Visualization — Watch your agent swarm’s Git activity in real time. Clear. Visual. Instant. Run: clawteam board gource --live See every commit, branch, and merge as it happens. Track what each agent is doing. 2) - Runtime Profiles — A provider‑aware configuration system. Switch between Claude, Kimi, and Gemini anytime. No need to edit environment variables. Run clawteam profile wizard. Follow the interactive setup. Done in minutes. 3) - Git-Based Context — Full worktree isolation with built‑in conflict detection and change tracking. Each agent works on its own branch, and the leader can see everything clearly in one place. 4) - Stability & Hardening — Spawn/workspace conflict fixes, improved tmux integration, message normalization, P2P liveness with lease-based detection. This release is about making the foundation rock-solid. --------------------------------------------------------- To show what a coordinated agent swarm can actually do, we ran 1 Claude Code orchestrating 8 Claude Code agents to build a robotics simulation system optimized for Apple Silicon — from scratch. 8 hours. 300+ PRs. One running simulator. Check the result: --------------------------------------------------------- Huge thanks to the open-source community for the feedback, issues, and PRs that shaped this release. ClawTeam is built in the open because we believe multi-agent coordination should be a shared primitive, not a proprietary moat. Try it: pip install clawteam Docs: GitHub: #ClawTeam #nanobot #AIAgents #openclaw #ClaudeCode #Cursor

Chao Huang

25,232 просмотров • 5 месяцев назад