DEV Community

Cover image for I Replaced OpenClaw with a $10 Device — This Tiny AI Agent Uses 99% Less Memory
brooks wilson
brooks wilson

Posted on

I Replaced OpenClaw with a $10 Device — This Tiny AI Agent Uses 99% Less Memory

#ai #openclaw #programming #productivity

I Replaced OpenClaw with a $10 Device — This Tiny AI Agent Uses 99% Less Memory

Like many developers, I’ve always wanted a 24/7 AI assistant running at home.

Something always-on.

Something lightweight.

Something that doesn’t require a Mac mini or a cloud server running all day.

But there was one problem:

OpenClaw is just too heavy.

High memory usage.

Slow cold starts.

Always-on electricity or cloud bills.

So I kept wondering:

Can an AI agent run on literal “e-waste” hardware?

Turns out — yes.

And it costs about $10.

Meet PicoClaw

Sipeed recently released an open-source project called PicoClaw.

It’s basically:

👉 a super lightweight OpenClaw alternative

👉 rewritten from scratch in Go

👉 runs in under 10MB RAM

For comparison:

  • 99% less memory than OpenClaw
  • 98% cheaper than keeping a Mac mini online

That’s honestly kind of insane.

Why This Matters

This isn’t just “smaller”.

It changes where AI agents can run.

You can deploy it on:

  • Raspberry Pi 3B
  • old Android TV boxes
  • cheap RISC-V boards
  • NanoKVM
  • even routers (theoretically)

I tested it on an old Raspberry Pi and it booted almost instantly with barely any RAM usage.

This is what real Edge AI looks like.

Key Features

  • < 10MB memory usage
  • boots in under 1 second
  • 400× faster startup
  • single self-contained binary
  • runs on RISC-V / ARM / x86
  • no Node.js
  • no Python environment
  • no dependency hell

Just drop one file and run.

As a developer, this feels incredibly refreshing.

What Can It Do?

Despite the tiny footprint, it keeps the three core elements of an AI agent:

Perception · Thinking · Action

Messaging platforms

Telegram, Discord, QQ, DingTalk

Tool execution

  • run shell commands
  • read/write files
  • automate workflows

Voice + Web

  • Whisper (via Groq) for speech-to-text
  • Brave Search for internet search

So it can hear and see.

Not bad for a $10 device.

Installation & Deployment

If you want to try it yourself, here are the full setup steps.

Option 1 — Prebuilt binary (easiest)

Download directly from Releases and run.

Option 2 — Build from source 

git clone https://github.com/sipeed/picoclaw.git
cd picoclaw
make deps

# build
make build

# multi-platform build
make build-all

# build and install
make install
Enter fullscreen mode Exit fullscreen mode

Option 3 — Docker (recommended for servers) 

git clone https://github.com/sipeed/picoclaw.git
cd picoclaw

cp config/config.example.json config/config.json
vim config/config.json   # add your API keys

docker compose --profile gateway up -d
docker compose logs -f picoclaw-gateway
Enter fullscreen mode Exit fullscreen mode

Stop:

docker compose --profile gateway down
Enter fullscreen mode Exit fullscreen mode

Agent mode 

docker compose run --rm picoclaw-agent -m "What is 2+2?"
docker compose run --rm picoclaw-agent
Enter fullscreen mode Exit fullscreen mode

Configuration

Default path:

~/.picoclaw/config.json
Enter fullscreen mode Exit fullscreen mode

Initialize:

picoclaw onboard
Enter fullscreen mode Exit fullscreen mode

Example:

{
  "agents": {
    "defaults": {
      "workspace": "~/.picoclaw/workspace",
      "model": "glm-4.7",
      "max_tokens": 8192,
      "temperature": 0.7
    }
  }
}
Enter fullscreen mode Exit fullscreen mode

CLI Usage 

picoclaw agent -m "Hello"
picoclaw gateway
Enter fullscreen mode Exit fullscreen mode

You now have a tiny, always-on personal AI assistant.

Technical Thoughts

Most agent frameworks use:

  • TypeScript
  • Python

Which often means:

  • heavy dependencies
  • high memory
  • slow cold start
  • complex environments

PicoClaw’s Go + single binary design removes all of that.

If OpenClaw feels like a full operating system…

PicoClaw feels like a microkernel.

Minimal. Efficient. Practical.

Final Thoughts

This project convinced me that:

You don’t need massive compute to run agents.

Let the LLM handle reasoning via API.

Let a tiny runtime handle orchestration.

That’s enough.

And much cheaper.

If you’re exploring Edge AI, Raspberry Pi automation, or low-cost home lab AI, PicoClaw is absolutely worth trying.

Links of picoclaw

GitHub

https://github.com/sipeed/picoclaw

Website

https://picoclaw.org/

Top comments (0)