Why Silicon Valley Is Stockpiling Mac Minis: A Week with the AI Agent Moltbot

The Real Reason Silicon Valley Is Currently Stockpiling Mac Minis

The atmosphere in the US tech scene has been quite unusual lately. Out of nowhere, among developers in San Francisco, a “Mac Mini shortage” is happening.

It’s common for Apple Store deliveries to be delayed by several weeks, and on secondhand markets, models with M4 and M5 chips are sold out as soon as they appear. It’s not even a new iPhone release — so why has this quiet desktop suddenly become such a hot item?

Key Point: People aren’t buying this machine as a “computer.” They’re purchasing this small, boxy device as a ‘dormitory for digital workers’.

At the heart of this is an AI agent that’s turned the open-source ecosystem upside down: “Moltbot”. Today, I want to share my honest experience of installing Moltbot on my Mac Mini — which was slowly turning into a Netflix machine — and using it as a “wage-less employee” for a week.

Quick Summary: Why Mac Mini + AI Agent?

Below, I compare the traditional AI usage methods with the Mac Mini + Moltbot combo. The key shift is from “ask AI and execute manually” to “AI completes the execution automatically.” Pay special attention to the cost aspect.

The Era of Chatbots Is Over — Now It’s All About ‘Agents’

What we’ve been excited about — ChatGPT, Claude, Gemini — were essentially “smart chat partners”. When asked to generate code, they’d display text on the screen, but copying that code into files and running it was still a tedious human task.

But Moltbot is fundamentally different. Its slogan is “AI with Hands”. Moltbot escapes the prison of the browser and directly interacts with my computer’s OS:

I’ve summarized what Moltbot can actually do. Check the “Actual Examples” column in the table below — these are tasks I’ve personally commanded it to perform. Especially useful for developers are the development and data collection functions.

My Mac Started Working Overtime on Its Own (Real-World Usage)

Initially skeptical, I set up Moltbot on my local server (M4 Pro Mac Mini). I then entrusted it with my entire workflow for a week.

Case 1: Automating Morning Briefings

I usually spend about 30 minutes every morning reading newsletters, checking emails from overnight, and reviewing today’s calendar. I programmed Moltbot to handle this routine.

Moltbot’s Morning Briefing:

“Master, you received an important AWS billing alert email last night. Today’s 10 AM Zoom meeting link has changed, so I’ve updated your calendar. Also, I’ve summarized three recent papers on ‘On-Device AI’ and saved them in the ‘Reading List’ folder.”

Case 2: Coding? No, Supervising

The most astonishing moment was when I asked it to run a Python script:

“Create a crawler that scrapes Naver News economic headlines and saves them to Excel.”

I compared the step-by-step process of doing this with ChatGPT versus Moltbot. The “Time Taken” row clearly shows why agents are revolutionary.

During the process, an error occurred: “Element not found.” Before I could intervene, Moltbot displayed a log: “HTML structure changed, will fix it.” It then autonomously corrected the code and generated the file.

Why the Mac Mini, Specifically?

This reveals the economic reason behind why developers in the US are stockpiling Mac Minis. Running a “resident” AI agent like Moltbot requires specific conditions:

I compared three options for 24/7 AI operation: Mac Mini, Windows gaming PC, and cloud server. Focus on power consumption and monthly costs. It’s clear why Mac Minis are so efficient.

Ultimately, the Mac Mini isn’t just a computer — it’s the perfect “employee” who doesn’t need a salary or much electricity, yet works 24/7″.

Breaking Free from SaaS Subscription Fees

The more interesting part is the cost savings. We’ve been paying subscriptions to countless SaaS services for automation. But once you install Moltbot on a Mac Mini and connect an open-source LLM, all those subscription fees vanish.

I compared the monthly SaaS subscription costs with the costs after replacing them with Moltbot + local LLM. The last two rows show the total monthly and yearly savings, which are quite significant.

Installation Guide: Just 30 Minutes Needed

No need to worry if you’re not tech-savvy. If you can copy and paste in Terminal, you’re good to go.

What You Need

Before installing Moltbot, check the hardware requirements. “Minimum specs” will run it, but “recommended specs” provide a smoother experience. RAM is the most important.

Installation Steps

# 1단계: Homebrew 설치 (이미 있다면 스킵)
/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"
# 2단계: 필수 도구 설치
brew install git node python
# 3단계: 몰트봇 클론 및 설치
git clone <div class="link-preview" data-url="https://github.com/moltbot/moltbot.git">
                <div class="link-preview-content">
                    <div class="preview-image">
                        <img src="https://opengraph.githubassets.com/95ca893a713b25c6e9b243990d52234554632a6b25eee44d069587e94dacf375/openclaw/openclaw">
                    </div>
                    <div class="preview-content">
                        <div class="preview-title">GitHub - openclaw/openclaw: Your own personal AI assistant. Any OS. Any Platform. The lobster way. 🦞</div>
                        <div class="preview-description">Your own personal AI assistant. Any OS. Any Platform. The lobster way. 🦞  - GitHub - openclaw/openclaw: Your own personal AI assistant. Any OS. Any Platform. The lobster way. 🦞</div>
                    </div>
                </div>
            </div><p><br></p>
cd moltbot
npm install
# 4단계: 실행
npm start

Connecting a Local LLM (Using Ollama)

# Ollama 설치
brew install ollama
# 추천 모델 다운로드
ollama pull llama3.2        # 범용 (8GB RAM 필요)
ollama pull qwen2.5:14b     # 한국어 강화 (16GB RAM 필요)
ollama pull codellama:34b   # 코딩 특화 (32GB RAM 필요)

Caution: It’s Not All Sunshine and Rainbows

Honestly, it’s not perfect. I’ll share some limitations I encountered over the week:

I’ve summarized the limitations and how to address them based on my actual experience with Moltbot. Be especially aware of hallucinations and security concerns. Use the “Response” column to manage risks.

Despite these limitations, delegating about 80% of repetitive tasks is already a revolutionary change.

Conclusion: From Search to Delegation

After a week of experimentation, one thought stands out:

“We are moving from the era of Search to the era of Delegation.”

Previously, I’d Google questions and manually piece together information. Now, I can just say, “Find this for me,” or “Organize this,” and focus on more creative, important work.

Key Takeaways

It was a lengthy read, so here’s a concise summary of the core points. Keep this table in mind — it’s enough to understand the main idea.

If you have a dusty Mac gathering dust or just binge-watching Netflix, try installing Moltbot today. That tiny aluminum box might suddenly come alive as a partner that breathes and works for you.