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Cursor now natively supports git worktrees. You can run multiple agents in parallel, each with their own isolated copy of the codebase. This is great for comparing models or running the same model multiple times and picking the best result.

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Lee Robinson

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157,666 görüntüleme • 11 ay önce •via X (Twitter)

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Ollama 0.2 is here! Concurrency is now enabled by default. This unlocks 2 major features: Parallel requests Ollama can now serve multiple requests at the same time, using only a little bit of additional memory for each request. This enables use cases such as: - Handling multiple chat sessions at the same time - Hosting code completion LLMs for your team - Processing different parts of a document simultaneously - Running multiple agents at the same time Run multiple models Ollama now supports loading different models at the same time. This improves several use cases: - Retrieval Augmented Generation (RAG): both the embedding and text completion models can be loaded into memory simultaneously. - Agents: multiple versions of an agent can now run simultaneously - Running large and small models side-by-side Models are automatically loaded and unloaded based on requests and how much GPU memory is available.
0:23

Ollama 0.2 is here! Concurrency is now enabled by default. This unlocks 2 major features: Parallel requests Ollama can now serve multiple requests at the same time, using only a little bit of additional memory for each request. This enables use cases such as: - Handling multiple chat sessions at the same time - Hosting code completion LLMs for your team - Processing different parts of a document simultaneously - Running multiple agents at the same time Run multiple models Ollama now supports loading different models at the same time. This improves several use cases: - Retrieval Augmented Generation (RAG): both the embedding and text completion models can be loaded into memory simultaneously. - Agents: multiple versions of an agent can now run simultaneously - Running large and small models side-by-side Models are automatically loaded and unloaded based on requests and how much GPU memory is available.

ollama

219,488 görüntüleme • 2 yıl önce

AgentFS copy-on-write overlay in action 🔥 Multiple AI agents working on the same codebase. Each with isolated changes, zero conflicts. Host files stay untouched.
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AgentFS copy-on-write overlay in action 🔥 Multiple AI agents working on the same codebase. Each with isolated changes, zero conflicts. Host files stay untouched.

Pekka Enberg

62,741 görüntüleme • 9 ay önce

Using managed agents is perfect for running coding agents anywhere in the world. The beauty of this: • You can resume a session from anywhere • You can fork a session into multiple agents • You can run parallel agents • You can reuse environments Here is how you can do this with Claude Code, Codex, OpenCode, or Hermes.
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Using managed agents is perfect for running coding agents anywhere in the world. The beauty of this: • You can resume a session from anywhere • You can fork a session into multiple agents • You can run parallel agents • You can reuse environments Here is how you can do this with Claude Code, Codex, OpenCode, or Hermes.

Santiago

15,931 görüntüleme • 29 gün önce

Tip: You can run multiple code agents in parallel. Works well with Gemini CLI, Claude Code + git-worktree.
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Tip: You can run multiple code agents in parallel. Works well with Gemini CLI, Claude Code + git-worktree.

Addy Osmani

268,087 görüntüleme • 1 yıl önce

Maximizing your token throughput is one of the biggest productivity unlocks in Claude Code. So here's my guide to use multiple Claude Codes at the same time, effectively: - Run multiple Claude Code sessions at the same time, each on a different feature (Ghostty is great for this) - Use Claude Code's built in git worktrees to keep each instance isolated on its own branch (-w or --worktree flag) - Let Claude handle creating PRs or merging the worktree branches when you're done - Use the Claude Code Desktop app as your multi-agent control center Full guide below:
2:44

Maximizing your token throughput is one of the biggest productivity unlocks in Claude Code. So here's my guide to use multiple Claude Codes at the same time, effectively: - Run multiple Claude Code sessions at the same time, each on a different feature (Ghostty is great for this) - Use Claude Code's built in git worktrees to keep each instance isolated on its own branch (-w or --worktree flag) - Let Claude handle creating PRs or merging the worktree branches when you're done - Use the Claude Code Desktop app as your multi-agent control center Full guide below:

Avthar

10,754 görüntüleme • 6 ay önce

Grok Build tip of the day: worktrees! If you're unfamiliar with worktrees, they're essentially lightweight copies of your repo, allowing you to run parallel agents within their own workspaces. Try it either in the home screen or using `grok -w`!
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Grok Build tip of the day: worktrees! If you're unfamiliar with worktrees, they're essentially lightweight copies of your repo, allowing you to run parallel agents within their own workspaces. Try it either in the home screen or using `grok -w`!

akshey

2,551,425 görüntüleme • 4 ay önce

Having ChatGPT edit in Xcode is a game-changer Can edit across multiple apps and works with 4.5. It's just missing the ability to read the codebase, write multiple files and agents. For now, Alex is a great alternative.
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Having ChatGPT edit in Xcode is a game-changer Can edit across multiple apps and works with 4.5. It's just missing the ability to read the codebase, write multiple files and agents. For now, Alex is a great alternative.

Meng To

40,579 görüntüleme • 1 yıl önce

With the Codex app you can: - Multitask effortlessly: Work with multiple agents in parallel and keep agent changes isolated with worktrees - Create & use skills: package your tools + conventions into reusable capabilities ⁃ Set up automations: delegate repetitive work to Codex with scheduled workflows in the background
2:12

With the Codex app you can: - Multitask effortlessly: Work with multiple agents in parallel and keep agent changes isolated with worktrees - Create & use skills: package your tools + conventions into reusable capabilities ⁃ Set up automations: delegate repetitive work to Codex with scheduled workflows in the background

OpenAI

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Did you know? You can run agents in parallel in the GitHub Copilot app. Each session gets its own Git worktree and context, so you can build, review, and test all at the same time. Here's how to get started 👇
2:39

Did you know? You can run agents in parallel in the GitHub Copilot app. Each session gets its own Git worktree and context, so you can build, review, and test all at the same time. Here's how to get started 👇

GitHub

89,746 görüntüleme • 26 gün önce

Why settle for one Claude Code when you can run ten in parallel? We built Claude Squad — a manager for Claude Code & Aider tasks: • Supervise multiple agents in one place • Isolated git workspaces Free + open-source:
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Why settle for one Claude Code when you can run ten in parallel? We built Claude Squad — a manager for Claude Code & Aider tasks: • Supervise multiple agents in one place • Isolated git workspaces Free + open-source:

mufeez

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We’re introducing the Cursor SDK so you can build agents with the same runtime, harness, and models that power Cursor. Run agents from CI/CD pipelines, create automations for end-to-end workflows, or embed agents directly inside your products.
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We’re introducing the Cursor SDK so you can build agents with the same runtime, harness, and models that power Cursor. Run agents from CI/CD pipelines, create automations for end-to-end workflows, or embed agents directly inside your products.

Cursor

3,056,418 görüntüleme • 5 ay önce

New in M365 Copilot: Council. You can run multiple models on the same prompt at the same time, so you can see where they align and diverge, and understand what each adds.
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New in M365 Copilot: Council. You can run multiple models on the same prompt at the same time, so you can see where they align and diverge, and understand what each adds.

Satya Nadella

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We’re excited to launch the Codex app, a command center for building with agents. It gives you a focused space to manage multiple agents at once, run work in parallel, and collaborate with agents over long-running tasks.
4:21

We’re excited to launch the Codex app, a command center for building with agents. It gives you a focused space to manage multiple agents at once, run work in parallel, and collaborate with agents over long-running tasks.

OpenAI Developers

1,307,857 görüntüleme • 8 ay önce

takes vibe-coding a step further. Parallel AI teams, running directly in your browser. You can watch multiple agents think, build, and compete in real time, then pick the best result. Built by the Atoms.Dev and OpenManus teams. 3 wild use cases 🧵↓
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takes vibe-coding a step further. Parallel AI teams, running directly in your browser. You can watch multiple agents think, build, and compete in real time, then pick the best result. Built by the Atoms.Dev and OpenManus teams. 3 wild use cases 🧵↓

Charly Wargnier ♨️

63,856 görüntüleme • 9 ay önce

THIS IS HOW A SENIOR ENGINEER ACTUALLY SCALES THEMSELVES WITH CLAUDE CODE the biggest change with AI isn't coding faster. it's where you actually spend your time now. more detailed prompts, more code review, more planning, less typing, etc. here's the workflow: this guy has been shipping code since the days of cgi and perl. he uses a compound engineering plugin that runs 5 separate agents on every task. one brainstorms, one plans the technical implementation, one executes, one reviews, one checks different verticals. every step is documented in markdown files. it's slow and way more waiting. but the output quality is way higher because each agent is focused on one thing. then the REAL multiplier is in git worktrees if Claude Code made you 10x faster, worktrees multiplies that again depending on how many agents you can manage in parallel his team runs 4-8 Claude Code sessions at the same time across different worktrees with each one working on a separate task. the skill is managing multiple AI agents in parallel without losing track, that's the next evolution of engineering
0:56

THIS IS HOW A SENIOR ENGINEER ACTUALLY SCALES THEMSELVES WITH CLAUDE CODE the biggest change with AI isn't coding faster. it's where you actually spend your time now. more detailed prompts, more code review, more planning, less typing, etc. here's the workflow: this guy has been shipping code since the days of cgi and perl. he uses a compound engineering plugin that runs 5 separate agents on every task. one brainstorms, one plans the technical implementation, one executes, one reviews, one checks different verticals. every step is documented in markdown files. it's slow and way more waiting. but the output quality is way higher because each agent is focused on one thing. then the REAL multiplier is in git worktrees if Claude Code made you 10x faster, worktrees multiplies that again depending on how many agents you can manage in parallel his team runs 4-8 Claude Code sessions at the same time across different worktrees with each one working on a separate task. the skill is managing multiple AI agents in parallel without losing track, that's the next evolution of engineering

Om Patel

159,908 görüntüleme • 6 ay önce

Meet Replit Parallel Agents Build faster by running up to 10 agents in parallel Each agent gets its own copy of your app They work on their own computer Then merge their work agentically
1:16

Meet Replit Parallel Agents Build faster by running up to 10 agents in parallel Each agent gets its own copy of your app They work on their own computer Then merge their work agentically

Replit ⠕

709,808 görüntüleme • 5 ay önce

Claude Code has 3 models. Stop making Sonnet do Haiku’s job. Sonnet 5.5 builds. Haiku 5.5 scouts. Opus 5.5 reviews. Put them in parallel Git worktrees and let each model do what it’s best at. The setup: → Sonnet 5.5: Build features across isolated worktrees, writing code and running tests without touching your main branch. → Haiku 5.5: Explore the repo, index the AST, find dependencies, and scout for implementation paths while Sonnet codes. → Opus 5.5: Review architecture before implementation, investigate repeated test failures, and verify diffs before merging. Launch separate sessions: claude --worktree feat-auth claude -w feat-scout --model haiku Each session gets its own working directory and Git branch. Your agents can edit files and run tests in parallel without overwriting each other’s work. The full setup goes further: .worktreeinclude shares local configs across worktrees. Auto-cleanup keeps finished sessions tidy. Supervisor checkpoints catch contract drift and repeated test failures. A cwt alias makes launching new worktrees one command. Opus reviews the final diff before anything reaches main. The goal is simple: stop wasting expensive model calls on repo exploration, stop serializing work that can run in parallel, and stop merging code without a proper review. Paste the setup prompt into Claude Code. Ask it to show every config diff first, then approve the changes before anything gets edited. Build with Sonnet. Scout with Haiku. Review with Opus. Ship in parallel.
0:25

Claude Code has 3 models. Stop making Sonnet do Haiku’s job. Sonnet 5.5 builds. Haiku 5.5 scouts. Opus 5.5 reviews. Put them in parallel Git worktrees and let each model do what it’s best at. The setup: → Sonnet 5.5: Build features across isolated worktrees, writing code and running tests without touching your main branch. → Haiku 5.5: Explore the repo, index the AST, find dependencies, and scout for implementation paths while Sonnet codes. → Opus 5.5: Review architecture before implementation, investigate repeated test failures, and verify diffs before merging. Launch separate sessions: claude --worktree feat-auth claude -w feat-scout --model haiku Each session gets its own working directory and Git branch. Your agents can edit files and run tests in parallel without overwriting each other’s work. The full setup goes further: .worktreeinclude shares local configs across worktrees. Auto-cleanup keeps finished sessions tidy. Supervisor checkpoints catch contract drift and repeated test failures. A cwt alias makes launching new worktrees one command. Opus reviews the final diff before anything reaches main. The goal is simple: stop wasting expensive model calls on repo exploration, stop serializing work that can run in parallel, and stop merging code without a proper review. Paste the setup prompt into Claude Code. Ask it to show every config diff first, then approve the changes before anything gets edited. Build with Sonnet. Scout with Haiku. Review with Opus. Ship in parallel.

Arindam Majumder 𝕏

14,192 görüntüleme • 10 gün önce

As soon as you try to run 2 agents on the same data, everything breaks: • Agent 1 reads some data and starts working. • Two seconds later, Agent 2 changes that same data. This is a problem. Agents will waste tokens on stale data, overwrite each other's work, and redo tasks the other has already finished. You can't prompt your way out of this mess. Everything old in software engineering is new again. We need proper coordination when running multiple agents. Here is a good open-source solution for this: Omnigraph is a graph database for context assembly and multi-agent coordination. Here is how it works: • It sets one shared place where multiple agents will work from • Each agent gets their own copy of the data • Agents write their changes to their copy • When an agent is done, it merges its changes back Three huge benefits from this model: 1. We know it works. We've been doing this for decades already. 2. No more lost information or agents stepping on each other's toes. 3. You get a complete trail of which agent did what and when. I recorded a video to show you a bit more about this. Here is the link to the Omnigraph GitHub repository:
6:51

As soon as you try to run 2 agents on the same data, everything breaks: • Agent 1 reads some data and starts working. • Two seconds later, Agent 2 changes that same data. This is a problem. Agents will waste tokens on stale data, overwrite each other's work, and redo tasks the other has already finished. You can't prompt your way out of this mess. Everything old in software engineering is new again. We need proper coordination when running multiple agents. Here is a good open-source solution for this: Omnigraph is a graph database for context assembly and multi-agent coordination. Here is how it works: • It sets one shared place where multiple agents will work from • Each agent gets their own copy of the data • Agents write their changes to their copy • When an agent is done, it merges its changes back Three huge benefits from this model: 1. We know it works. We've been doing this for decades already. 2. No more lost information or agents stepping on each other's toes. 3. You get a complete trail of which agent did what and when. I recorded a video to show you a bit more about this. Here is the link to the Omnigraph GitHub repository:

Santiago

29,335 görüntüleme • 1 ay önce

It’s now easier to move local agents to the cloud so they can keep working with your laptop closed. Prompt Cursor from your phone, run many agents in parallel, and get back PRs with demos of their work.
0:28

It’s now easier to move local agents to the cloud so they can keep working with your laptop closed. Prompt Cursor from your phone, run many agents in parallel, and get back PRs with demos of their work.

Cursor

1,244,139 görüntüleme • 4 ay önce