@blueskylh1: The most painful thing about solo product development or leading an AI team is being a "mindless messenger" between different chat windows. After the PM writes the requirements, I have to copy and paste them into the developer's chat. After seeing the sharing from Jason @jxnlco, a developer experience engineer on the OpenAI Codex team, I set up a workflow without...

The most painful thing about solo product development or leading an AI team is being a "mindless messenger" between different chat windows. After the PM writes the requirements, I have to copy and paste them into the developer's chat. After seeing the sharing from Jason @jxnlco, a developer experience engineer on the OpenAI Codex team, I got a workflow that allows PM, backend, frontend, QA, and AI to collaborate efficiently using only local plain text files, without any complex code. This approach also works for different agent teams. (Using the development of an "Automated Overseas Tech News Weekly Tool" as an example, here is a complete step-by-step practical tutorial.) **Step 1: Set up a local file cabinet** Create a main folder `vault/` on your local computer or cloud drive, and create four empty subfolders inside: - `vault/projects/` (for core technical handover documents) - `vault/people/` (for team or contact requirements) - `vault/notes/` (for temporary memos and drafts) - `vault/agents/` (for AI employee handbooks) **Step 2: Add the master rule (AGENTS.md) to the root directory** Create a new file `AGENTS.md` in the root of `vault/` and directly copy and paste the rules from the comment section below. This is for all AI. (The specific content is posted in the comments section.) **Step 3: Distribute four job descriptions in agents/** In the `vault/agents/` directory, create four corresponding `.md` files and paste the following responsibilities: - **pm.md (Product Manager):** Responsibilities: Turn the owner's ideas into requirements. Has write access to `projects/`. Create and update `projects/product_spec.md` (requirements document), define features and acceptance criteria. - **backend.md (Backend Expert):** Responsibilities: Write core logic and APIs. Read-only access to requirements documents. Create and write `projects/api_design.md` (API document, define input/output parameters), and write core crawling and summarization code. - **frontend.md (Full-stack Frontend):** Responsibilities: Handle UI design and frontend code. Read both the requirements document and backend API document. You need to design the visual appearance of the entire UI, Tailwind layout, and write the interface code. Strictly avoid inventing data fields that don’t match the backend. - **qa.md (Test Expert):** Responsibilities: Run tests, catch bugs. Read all code and documents from the full pipeline. Create and write `projects/test_plan.md`, report unfixed bugs and tag frontend/backend for fixes. **Step 4: Run the development pipeline** Mount the `vault` folder in your AI tool (e.g., Codex), open 4 pinned conversations (Thread 1 to 4), and start the relay: 1. **Wake up the PM to gather requirements (Switch to Thread 1)** Instruction: "Read AGENTS.md and agents/pm.md. You are now officially the PM. I want to build an automated overseas tech news weekly tool. The core is to fetch hot posts on X and summarize them in plain geek language. Go." AI action: It will think in the background, automatically generate `projects/product_spec.md` locally. 2. **Wake up the backend to write logic (Switch to Thread 2)** Instruction: "Read AGENTS.md and agents/backend.md. Start as backend. Go read the PM's file, define the backend API for this weekly tool, and write the core crawling script." AI action: It reads the PM's document, writes `projects/api_design.md` locally, and finishes the Python crawling logic. 3. **Wake up the frontend to build the UI (Switch to Thread 3)** Instruction: "Read AGENTS.md and agents/frontend.md. Start as frontend. Go read the requirements and backend API, design the UI visual style and tech color scheme for the weekly page, then pixel-perfect implement with Next.js, matching the APIs." AI action: The frontend enters, holding requirements in one hand and backend API in the other. It designs the news card style and seamlessly stitches frontend and data with Tailwind CSS. 4. **Wake up the QA to catch bugs (Switch to Thread 4)** Instruction: "Read AGENTS.md and agents/qa.md. Start as QA. Go read the code and documents written by the previous team members, run automated tests, and report bugs in a test report." AI action: QA automatically runs tests. If long text overflows, it creates `projects/test_plan.md` locally with the record: [BUG #01] Text not truncated, causing overflow. Owner: @Frontend. Later, let the frontend take a look and fix it. Throughout the process, as the CTO, you only need to give orders in 4 windows without copying and pasting a single word of requirements or code. They collaborate asynchronously through local text building blocks. If this workflow helps you, feel free to follow, like, share, and comment so more agent teams can see it.