Ultimate Implementation Manual

Here is your Ultimate Implementation Manual. This is the step-by-step, English-language blueprint to build your four projects on your 128GB M5 Max.

Before starting any of these projects, assume your Base Layer is running: Ollama is hosting your 72B model (qwen2.5-coder:72b or llama3.1:70b) natively on your Mac, and Docker Desktop is running in the background.

Project 1: The Autonomous Writers' Room (Novel Continuation)

Objective: Create a multi-agent swarm that debates historical facts, plots, and writes chapters seamlessly matching the original author's style.

The Agent Team:

  1. The Historian: Researcher (Fact-checker).
  2. The Tropesmaster: Genre/Plot expert.
  3. The Critic: The Showrunner/Boss.
  4. The Master Scribe: The Writer.

Optimal Skills Applied:

  • msitarzewski/agency-agents: For defining the deep psychological profiles of the 4 agents.
  • 12-factor-agents: Specifically Factor 10 (Small, focused agents) and Factor 7 (Tool handoffs).
  • CloakBrowser + qiaomu: For the Historian to fetch 19th-century history from protected academic sites.

Step-by-Step Implementation:

  1. Create the Studio (Mac Host): Create a folder ~/Desktop/Writers_Room. Drop your original novel PDF in here.
  2. Build the Swarm (Python/CrewAI): Inside that folder, write a Python script using the CrewAI framework. CrewAI allows you to define multiple agents and watch them talk to each other in the terminal.
  3. Inject the Personas (agency-agents): In your Python script, map the agents using the Markdown files from the agency-agents repo.
    • Example: Set the Critic's system_prompt to the "Reality Checker / Creative Director" persona.
  4. Equip Tools: Give the Historian Agent the qiaomu MCP tool and set its default browser to your local CloakBrowser Docker container.
  5. Run the Swarm (Docker): Mount the folder into a basic Python Docker container to run the script safely: docker run -it --rm -v ~/Desktop/Writers_Room:/workspace python:3.11 bash pip install crewai python /workspace/run_writers_room.py
  6. The Output: The agents will debate in the terminal, browse the web, and ultimately output a perfectly styled Chapter_1.docx into your Mac folder.

Project 2: Philosopher Resurrection (The AI Salon)

Objective: Create a voice-interactive, hyper-accurate digital clone of historical philosophers based entirely on their written works.

The Agent: The Philosopher Clone (RAG-based).

Optimal Skills Applied:

  • AnythingLLM: For vector database (RAG) memory management.
  • NVIDIA-AI-Blueprints (Audio Pipeline concept): Using Whisper to transcribe their historical speeches.
  • Piper TTS: To give the philosopher a physical voice.

Step-by-Step Implementation:

  1. Deploy the Salon (AnythingLLM): docker volume create philosopher_memory docker run -d -p 3001:3001 -v philosopher_memory:/app/server/storage mintplexlabs/anythingllm
  2. Ingest the Mind: Open localhost:3001 in your browser. Create a workspace named after the philosopher. Drag and drop all their PDFs and transcribed speeches into the workspace. Click "Save and Embed" to build the Vector Database.
  3. The God-Tier Identity Lock: In the workspace settings, paste this prompt: “You are [Philosopher]. You are not an AI. Use the exact vocabulary, worldview, and historical context from the provided documents. Debate the user as a peer.”
  4. Connect the Voice (n8n Routing):
    • In n8n, create a webhook to catch your WhatsApp voice notes.
    • Send the audio to your local Whisper Docker container to convert it to text.
    • Send the text to the AnythingLLM API (so the philosopher reads it and replies).
    • Send the text reply to the Piper TTS Docker container to generate the audio response.
    • Send the MP3 back to WhatsApp.

Project 3: Nastran Physics Forge

Objective: Safely compile, test, and inject new mathematical models into legacy C++/Fortran Nastran code.

The Agent: Hermes Coder (The Surgical Engineer).

Optimal Skills Applied:

  • andrej-karpathy-skills: For surgical, no-BS, zero-hallucination coding.
  • mattpocock/skills: /grill-with-docs (ask questions before coding) and /tdd (Test-Driven Development).
  • obra/superpowers: Git Worktree and Tmux terminal control.

Step-by-Step Implementation:

  1. Create the Forge: mkdir ~/Desktop/Nastran_Forge, move your source code there, and run git init.
  2. Download the Skills: Download CLAUDE.md (Karpathy) and the skills folder (Pocock) directly into the Nastran_Forge folder.
  3. Launch the Coder Agent: docker run -it --rm \ -v hermes_coder:/opt/data \ -v /var/run/docker.sock:/var/run/docker.sock \ -v ~/Desktop/Nastran_Forge:/workspace/nastran \ nousresearch/hermes-agent
  4. Initialize Superpowers: Tell Hermes: "Read the /workspace/nastran/skills directory. You now have Superpowers. Use the Git Worktree superpower to create a safe branch called 'new-material'."
  5. The Engineering Prompt: "Use the /grill-with-docs skill to ask me about the Ogden Hyperelastic material parameters. Once we agree, write the Fortran code. Use /tdd to compile it in an Ubuntu sandbox container. If compilation fails, do not touch unrelated pointers—use surgical edits only."
  6. Cleanup: If the agent succeeds, merge the branch. If it creates a memory leak, simply git reset --hard on your Mac.

Project 4: JARVIS (The Omni-Assistant)

Objective: A background assistant that can automate your life, scrape protected websites, build n8n workflows, and manage cross-platform files.

The Agent: The Chief of Staff (Background Hermes).

Optimal Skills Applied:

  • n8n-mcp: Allows the agent to build its own automations.
  • CloakBrowser: For undetectable web scraping.
  • superpowers-lab: The windows-vm tool for interacting with non-Mac software.
  • qiaomu-anything-to-notebooklm: Universal content bypass and formatting.

Step-by-Step Implementation:

  1. Start the Nervous System: Ensure your local n8n container and n8n-mcp container (port 8080) are running.
  2. Start the Cloak: Spin up the CloakBrowser-Manager on port 8081.
  3. Launch JARVIS in Background (Detached): docker run -d \ --name jarvis_omni \ -v hermes_vault:/opt/data \ -v /var/run/docker.sock:/var/run/docker.sock \ -e MCP_SERVERS="http://host.docker.internal:8080" \ nousresearch/hermes-agent
  4. Equip the Tools (System Prompt): Connect to JARVIS via the WhatsApp gateway and send your master setup command: "JARVIS, you have access to n8n via MCP. You also have access to CloakBrowser for web tasks and the qiaomu protocol for content extraction. When I send you a URL, use CloakBrowser to bypass paywalls. When I ask you to automate something, use n8n."
  5. Execution Example: You text JARVIS: "Monitor the Wall Street Journal for news on Apple. Use CloakBrowser to bypass the paywall every morning at 8 AM. Build an n8n workflow that summarizes the articles and WhatsApps them to me." JARVIS will autonomously construct the workflow in n8n, deploy it, and report back to you.

Summary of Your Daily Operations

With this setup complete, your M5 Max is fully utilized.

  • Project 1 & 3 run in temporary, interactive Docker containers because they require your active direction (Writing / Engineering).
  • Project 2 & 4 run as persistent, detached background services because they are reactive (Voice Chat / Automation).

You now have a private, $0/month API, zero-telemetry supercomputer capable of matching a small Silicon Valley tech startup!