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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...

32,313 просмотров • 3 месяцев назад •via X (Twitter)

Комментарии: 27

Фото профиля Sesori - Claude, Codex & OpenCode on Mobile
Sesori - Claude, Codex & OpenCode on Mobile3 месяцев 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 Poniatowski3 месяцев назад

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

Фото профиля Sakata
Sakata3 месяцев назад

Bookmarkedddd will watch when I’m free

Фото профиля Liam | AI Tools & News
Liam | AI Tools & News3 месяцев назад

Helpful

Фото профиля MIKE
MIKE3 месяцев назад

I’m happy to hear that

Фото профиля MAIL
MAIL3 месяцев назад

damn great step by step guide

Фото профиля 安叫兽|Bird🕊️ 🔶 BNB
安叫兽|Bird🕊️ 🔶 BNB3 месяцев назад

worktree 这招真挺适合并行折腾的

Фото профиля Vipul Kumar Kewat
Vipul Kumar Kewat3 месяцев 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
DAVE3 месяцев назад

oh wow

Фото профиля Coscosmico
Coscosmico3 месяцев назад

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

Фото профиля Diario฿itcoin
Diario฿itcoin3 месяцев назад

All I see is merge hell.

Фото профиля Jurly
Jurly3 месяцев 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
LarpRom3 месяцев назад

Good orchestration beats throwing everything at one agent.

Фото профиля Blum
Blum3 месяцев назад

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

Фото профиля creeeeng
creeeeng3 месяцев назад

stack bloat feels productive lol tbh

Фото профиля FlowOps Daily
FlowOps Daily3 месяцев 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.eth3 месяцев назад

the review agent is my favorite part

Фото профиля cbrd21-1("bird")
cbrd21-1("bird")3 месяцев 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 Adeyemo3 месяцев назад

Oh man this is a huge Graph Engineering Masterclass

Фото профиля The AI Therapist
The AI Therapist3 месяцев назад

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

Фото профиля ceek
ceek3 месяцев назад

let’s get it

Фото профиля 𝐕𝖆𝖑𝖊𝖓𝖙𝖎𝖓𝖔~❍𝖓𝖈𝖍𝖆𝖎𝖓.𓄀
𝐕𝖆𝖑𝖊𝖓𝖙𝖎𝖓𝖔~❍𝖓𝖈𝖍𝖆𝖎𝖓.𓄀3 месяцев назад

Alot of steps.

Фото профиля catman
catman3 месяцев 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
Leo3 месяцев назад

smooth workflow here mate

Фото профиля Innopro
Innopro3 месяцев назад

What they built is interesting

Фото профиля stanley
stanley3 месяцев назад

insane work jesus.

Фото профиля mike
mike3 месяцев назад

wow insane bro bookmarked

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this is pure f*cking treasure 10 GitHub repos with 165K+ combined stars to build your own AI agent team that works 24/7 most people still use one AI chat for everything. these repos turn Claude into a whole team: one agent researches, one codes, one reviews, and a lead runs them all one resource per step, from your first 3 agents to a full swarm running Claude and Codex together (1/10) CrewAI the easiest way to assemble a team of agents: give them roles and tasks, then hit kickoff ▸ (2/10) LangGraph connect agents into a graph with checkpoints, so if something fails it resumes instead of starting over ▸ (3/10) wshobson/agents ready-made agents for Claude Code (backend, frontend, security, tests, devops) plus an orchestrator to run them ▸ (4/10) oh-my-team 12 specialist agents for Claude Code that split the work and merge the results ▸ (5/10) agent-swarm your own self-hosted AI company: one lead agent hires workers and runs them 24/7 ▸ (6/10) Open-Agents spawns many Claude agents in parallel, so 6 tasks run at once instead of one after another ▸ (7/10) swarms an enterprise-grade framework for when your team grows from 5 agents to 50 ▸ (8/10) Microsoft Agent Framework Microsoft's new framework, the AutoGen successor, for workflows, agents and runtime in one place ▸ (9/10) CLI Agent Orchestrator runs Claude, Codex and other CLIs side by side as one team, with a supervisor watching all of them ▸ (10/10) ensemble launches Codex and Claude together, so they build and ship as one ▸ the loop: assemble → plug in → run → scale → orchestrate pick one, click, let it run, and while everyone else is still typing prompts, your agents are already shipping ↓

Noisy

14,563 просмотров • 11 дней назад

I can't f*cking believe people still use Claude Code like a chat bot. the ones getting real work out of it gave it a folder, tools and a map of everything it knows. that map is graphify. you point it at a folder and it builds a knowledge graph of everything inside. code, docs, PDFs, images, even video. then your agent searches the graph instead of opening files one by one. 134k stars on GitHub. backed by Y Combinator. and most people still haven't tried it. what makes it different: -> the code part runs fully on your machine. nothing gets uploaded -> no vector database, no embeddings. it's a real graph your agent walks through -> every connection is labeled: read straight from the source, or figured out by graphify. you always know which -> you get 3 files: a clickable map you open in your browser, a report with the key ideas and surprising links, and the full graph your agent queries anytime on a public memory benchmark it found the right answer in its top 10 results about half the time. mem0 managed under 5%. and building the graph cost 0 model credits. here's the full setup around it: > create a folder called AGENT, open Claude Code inside it, and add a CLAUDE.md with one line: "save every decision, person and project to memory/" > run uv tool install graphifyy, then graphify install, then type /graphify . and the whole folder becomes a map Claude can search in seconds > run npm install -g @googleworkspace/cli, then gws auth setup and gws auth login. Claude can now read your Gmail, Calendar and Drive > run claude mcp add playwright npx @playwright/mcp@latest. it gets its own browser for sites, forms and data > run npm i -g jev-guard, then jev-guard key "...", then jev-guard install claude. Jev checks every action before it runs. rm -rf gets blocked, emails with hidden instructions get flagged, about 4 cents per 1,000 checks > type /schedule and say "every morning at 7:30, send me what came in, what you drafted and what needs my yes" one folder. 15 minutes. and Claude finally knows where everything is. all the repos: -> -> -> -> bookmark this and try graphify first. it's the piece everyone skips.

kiosa

26,006 просмотров • 2 дней назад