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Tue, Jun 2, 2026 5picks
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17:18

A Multi-Agent IDE to Run Claude Code, Codex, and Others in Parallel Git Worktrees

多代理并行 IDE：在一个工作区同时调度 Claude Code、Codex 等 AI 编程代理

Orca is a desktop and mobile IDE designed to run multiple AI coding agents—such as Claude Code, Codex, and Grok—concurrently. It leverages Git's worktree mechanism to give each agent an isolated working directory, eliminating the need for stashing or branch juggling. Users can observe and control all agents from a single interface with tabbed panes, built-in diff review, and direct GitHub Issue/PR integration. It's built for developers who rely on CLI-based coding agents and need to handle multiple features or refactors in parallel.

github.com · 9 min · Agents · Ai Tooling · CLI · Developer Tools · Git Worktree · IDE
09:34

Understand Anything: Turn any codebase into an interactive knowledge graph you can explore

Understand Anything：把任何代码库变成可交互的知识图谱

Understand Anything is an open-source tool that turns any codebase into an interactive knowledge graph for exploration, search, and query. Instead of static diagrams, it builds a persistent, navigable knowledge base that integrates with AI coding tools like Claude Code, Cursor, and Codex. It parses code structure and semantic relationships to make logical connections tangible, helping developers quickly onboard legacy systems, locate business logic, or navigate complex codebases.

github.com · 1 min · Agents · LLM
06:00

Why I Don’t Vibe Code

我为什么拒绝‘氛围编程’

The author refuses to vibe code because he is cheap, experienced, loves messy details, sees friction as a gift, and cares about quality and accountability. Drawing on Fred Brooks' No Silver Bullet, he argues that LLMs reduce only accidental complexity, not essential complexity. He highlights the danger of data abstraction without skepticism using DOGE’s misinterpretation of Social Security records. He insists that the joy and friction of programming are essential to good design. The essay also covers ethical concerns and the human cost of AI-driven development. A must-read for developers questioning the AI coding trend.

jacobharr.is · 26 min · LLM
06:00

How to build your own agent harness???

用可替换 Worker 构建你自己的 Agent 控制框架——iii 架构详解

iii proposes an alternative to monolithic agent frameworks: decomposing the harness into a set of independent workers on a shared WebSocket engine. Each of the 15 responsibilities (turn orchestration, auth, policy, approval, session, etc.) is a separate worker that registers functions and triggers on a common bus via iii.trigger(). The architecture makes every layer replaceable—swap the model catalogue by writing a worker that registers models::list, add a provider with provider::<name>::stream, without touching the rest of the stack. The post walks through the turn loop in detail, explaining how provisioning, streaming, tool execution, approval gating, and teardown work across workers. Concrete replacement examples include model catalogue, credential store, approval UI, and policy engine. The entire harness is open source (github.com/iii-hq/workers), with all workers operating under the same protocol, yielding full OpenTelemetry tracing. The key insight: 'build your own harness' means swapping workers, not forking a framework, enabling a slider between thin and thick setups.

x.com · 20 min · Agents · Framework · Workers
06:00

Kimi's Agent Swarm: 300 agents, one prompt, real file outputs.

300 个智能体，一个提示词，输出真实文件：Kimi 的隐藏利器

Kimi's Agent Swarm is an underused multi-agent orchestration system that turns one prompt into real file outputs—resumes, websites, datasets, reports—by coordinating up to 300 domain-specialized agents. This thread by @0xDepressionn shares concrete examples: 100 tailored CVs, a 100,000-word literature review, and 30 landing pages, each replacing thousands of dollars in professional labor. The author distills 15 actionable rules for harnessing Agent Swarm effectively: write project briefs, not questions; batch tasks for leverage; specify output format upfront; attach source files; and save repeatable workflows as Skills. The result is a shift from single-question chatbots to high-volume deliverable generation, making Kimi a cost-effective alternative to expensive services.

x.com · 12 min · Agents · AI · LLM