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Recipe for insane development speed: Git worktrees + AI agents = parallel coding superpowers While one agent fixes issue #361, another tackles #305, and a third investigates that user bug report—all without conflicts. This changes everything.

45,195 просмотров • 1 год назад •via X (Twitter)

Комментарии: 11

Фото профиля Kieran Klaassen
Kieran Klaassen1 год назад

See my scripts

Фото профиля Alexander Mia
Alexander Mia1 год назад

INTRODUCING: Agentic Security - LLM Security Scanner! 🔍 🔑 Features: Scans for prompt injections, jailbreaking & more. Provides detailed reports & options to customize attack rules. 🔗access the GitHub Link ↓

Фото профиля Iggy
Iggy1 год назад

I made for precisely this!

Фото профиля Courtland Allen
Courtland Allen1 год назад

I've been doing this but realizing that working in parallel, isn't that helpful on a regular basis. Like by the time I set up a new work tree, install dependencies, and describe my task to the AI, the AI is already done with what it was doing in the first work tree

Фото профиля Kieran Klaassen
Kieran Klaassen1 год назад

with ruby all of that ios cached so no overhead

Фото профиля Peter Steinberger
Peter Steinberger1 год назад

I experimented with worktree, claude works better with separate clones. I use 6 for my project.

Фото профиля Kieran Klaassen
Kieran Klaassen1 год назад

how is that different than a worktree? a worktree is just a copy of the files too right?

Фото профиля andrii
andrii1 год назад

great, and then who merges all this mess to main resolving all the inter-dependencies, conflicts and regressions?

Фото профиля Kieran Klaassen
Kieran Klaassen1 год назад

with good research before its really good

Фото профиля Freddie Vargus
Freddie Vargus1 год назад

you should check out

Фото профиля Kieran Klaassen
Kieran Klaassen1 год назад

Cool will do! Thanks

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Claude Code made developers 10x faster. Git worktrees just broke the speed limit again. Teams are now running 4–8 AI agents in parallel — each in its own branch — working at the same time. Not sequential. Not one prompt at a time. Parallel AI engineering. Here’s the shift: Old workflow: Prompt → wait → review → fix → repeat New workflow: Agent 1 → builds feature Agent 2 → writes tests Agent 3 → reviews security Agent 4 → refactors architecture Agent 5 → updates docs All running simultaneously. This is called compound engineering. You’re not using AI as a tool anymore — you’re managing a team of agents. Git worktrees make this possible: Each agent gets: • its own branch • its own workspace • its own context • its own task No conflicts. No overwriting. No chaos. Just parallel progress. The result? Claude makes you 10x faster. Parallel agents multiply that again. 10x → 30x → 50x productivity. Senior engineers are already doing this: brainstorm agent planning agent implementation agent review agent testing agent It’s basically CI/CD for thinking. And the weirdest part: This actually slows each step down but speeds the entire system up. More planning More reviewing More parallel execution = higher quality + faster delivery. We’re moving from: "prompt engineering" to: "agent orchestration" The new skill isn’t coding. It’s managing AI workers. The best engineers won’t write more code — they’ll run more agents. Bookmark this. Parallel AI development is the next meta

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