Gonka: Launching Decentralized AI GPU Node with Claude Code

A Note from Pieoneers: Why We're Sharing This

At Pieoneers, we build web and mobile applications for ambitious startups and established businesses across North America. With over 15 years of professional software development experience, we have worked with clients in fintech, healthcare, logistics, education, and beyond, tackling everything from MVP rapid development to enterprise integrations.

Our tech stack spans Node.js, React, Python, Go, Flutter, iOS, and Android. We have always prided ourselves on staying at the cutting edge of development practices, including AI integration.

Our AI transformation journey spans more than 5 years. We were applying machine learning to healthcare projects as early as 2019-2020, long before the current AI boom. But in the past 2-3 years, something fundamental has shifted in how we work. Not only in what we build, but in how we build it.

AI coding assistants have improved our development efficiency.

What started as experimental tools have become core to our daily workflow. Today, every developer on our team leverages AI code assistants: not as a replacement for expertise, but as a force multiplier that lets us tackle more ambitious projects, deliver faster, and maintain high quality standards.

Introduction

Gonka.ai is pioneering a new approach to decentralized AI infrastructure. Unlike GPU rental marketplaces like Akash or Render where you simply lease compute power, Gonka implements Proof of Compute 2.0, a validation economy where node operators earn tokens by verifying the quality and accuracy of AI inference work performed across the network. Think of it as running a validator node for blockchain networks, but instead of validating transactions, you're validating AI model outputs. What's fascinating is the economics: our H100 GPU node earns primarily through CPU-based validation work (checking other nodes' AI responses), not by running inference requests. In just 10 days, we have accumulated nearly 100,000 GONKA tokens (currently vesting over ~6.5 months) while helping secure a decentralized AI network.

This post documents our complete journey deploying a Gonka validator node – with a unique twist. We used Claude Code, Anthropic's AI coding assistant, for the entire process: parsing deployment documentation, troubleshooting Docker service crashes, building a custom real-time monitoring dashboard, and even understanding the tokenomics. What could have taken weeks of manual work, forum searching, and trial-and-error became a streamlined, well-documented deployment. We're sharing every step: the commands we ran, the problems we encountered, the solutions we discovered, and how AI-assisted development transformed infrastructure work from daunting to accessible.

Why This Gonka Setup Story Matters

The blog post you're about to read isn't a typical case study from our client portfolio. It's a real-world example of how AI-assisted development works in practice: not for a simple CRUD app or a standard web interface, but for an infrastructure setup that would traditionally require deep DevOps expertise.

Here is what makes this story relevant to our clients:

1. It Mirrors Real Project Challenges

Just like setting up a Gonka node, many of our client projects involve:

• Integrating with unfamiliar third-party systems
• Configuring infrastructure we haven't worked with before
• Debugging issues with sparse documentation
• Learning new technologies under time constraints

The traditional approach? Hire a specialist, extend timelines, increase costs.

2. It Demonstrates Practical Efficiency Gains

In this example:

• 8 hours (with Claude Code) vs 16-20 hours (manual ChatGPT-assisted approach)
• 4 hours to build a custom monitoring dashboard vs 4 days traditionally
• 3 minutes to debug and fix issues vs 30+ minutes of trial-and-error

These aren't theoretical improvements. This is the actual time saved on real tasks.

For our clients, this translates to:

✅ Faster MVP delivery

✅ Lower development costs

✅ More features within the same budget

✅ Ability to tackle more ambitious technical challenges

3. It Shows the Difference Between Chat AI and Agentic AI

Many of our clients ask: "Can't you just use ChatGPT for this?"

This story answers that question clearly. ChatGPT is phenomenal for brainstorming, learning concepts, and drafting code snippets. We use it daily.

But when it comes to:

• Reading actual files in your codebase
• Executing commands and verifying results
• Debugging in real-time
• Managing complex multi-file changes

You need agentic AI tools like Claude Code that can actually operate your infrastructure, not just advise about it.

The Pieoneers Vision for AI-Assisted Development

Our 5+ years of AI experience started with applying machine learning models to solve client problems including predictive analytics for healthcare, intelligent automation for logistics, and more. That taught us how AI could enhance what we build.

But the past 2-3 years have been transformative. AI coding assistants play a significant role in how we build. What began as cautious experimentation has become our standard workflow. Every project, every sprint, every developer on our team now leverages these tools daily.

We believe the future of software development isn't about replacing developers. It's about augmenting human expertise with AI execution capability.

For our development team, this means:

• Project managers can now tackle some development and  infrastructure tasks
• Senior developers can focus on architecture and business logic, not boilerplate
• Everyone spends less time on Stack Overflow and more time shipping features
• We can take on projects in new domains with confidence

For our clients, this means:

• We can take on ambitious projects without ballooning team size
• Faster iteration cycles (ship features weekly, not monthly)
• More resources available for design, user research, and innovation
• High quality code with built-in best practices shipped faster

For the industry, this means:

• Non-technical founders can validate technical ideas faster
• Smaller teams can compete with larger agencies
• Complex infrastructure becomes accessible to more people
• The barrier to entry for ambitious technical projects drops significantly

What to Expect from This Series

This Gonka setup story is the first in a series of real-world examples we'll be sharing about AI-assisted development at Pieoneers.

Upcoming posts will cover:

• How we use Claude Code for client mobile app development (React Native + Go backend)
• Integrating unfamiliar APIs in hours instead of days (payment gateways, healthcare systems)
• DevOps automation: Setting up CI/CD pipelines with zero prior experience
• Migrating legacy codebases with AI assistance
• Real cost comparisons: Traditional development vs AI-assisted on actual client projects

Who This Story Is For

If you're a potential client wondering:

• "How do I know Pieoneers can handle my unique tech stack?"
• "Can you really deliver an MVP in 8 weeks?"
• "Why are AI-assisted agencies more cost-effective?"

This post answers those questions by showing, not just telling.

If you're a developer or technical founder:

This story demonstrates what's now possible for teams (or individuals) who adopt the right tools. The barriers to running complex infrastructure have dropped dramatically.

If you're evaluating AI coding tools:

You'll see a practical, honest comparison of chat-based AI (ChatGPT) vs agentic AI (Claude Code) for real-world infrastructure work – not marketing claims, but actual time savings and challenges encountered.

A Quick Note on Authenticity

This isn't a sponsored post. We chose Claude Code because it solved a real problem for infrastructure work. Other excellent tools exist (Cursor, GitHub Copilot, Aider, etc.), and we evaluate new tools constantly.

What matters isn't the specific brand – it's the capability: tools that can read files, execute commands, and verify results are fundamentally different from tools that just provide advice.

Ready to See How This Works?

The blog post that follows is unfiltered: the mistakes, the dead ends, the hours spent debugging, and the moments where AI assistance made the difference between success and giving up.

Whether you're considering working with Pieoneers, evaluating AI tools for your own team, or just curious about decentralized AI infrastructure – this story has something for you.

About Pieoneers:

Pieoneers is an award-winning AI, web and mobile app development studio based in Vancouver, Canada. With over 15 years of professional experience and 5+ years of AI expertise, we build applications across fintech, healthcare, logistics, education, and more for clients throughout the US and Canada. We specialize in React, Node.js, Python, Go, Flutter, iOS, and Android development, with a focus on MVP rapid development and AI-assisted full-stack solutions.