Why GitHub Copilot is Overrated: Unpacking the Myths

As a solo founder, I was initially excited about the potential of GitHub Copilot to supercharge my coding productivity. After all, who wouldn't want an AI assistant that can help write code? However, after months of using it, I’ve come to realize that GitHub Copilot is often overrated. It doesn't quite deliver on the promises that are frequently touted online. This article unpacks the myths surrounding Copilot and offers a more grounded perspective for indie hackers and side project builders.

Myth 1: GitHub Copilot Can Replace Your Knowledge

Many advocates claim that Copilot can replace the need to fully understand programming concepts. In reality, it’s more of a code suggestion tool than an actual replacement for coding skills.

What it actually does:

Copilot suggests code snippets based on context, but it doesn’t understand your unique problem or the intricacies of your project.

Limitations:

• Lacks understanding of your project’s architecture.
• Often makes incorrect assumptions about what you need.

Our take:

We still rely heavily on our coding knowledge. Copilot is a supplement, not a substitute.

Myth 2: It’s Always Accurate

One of the biggest misconceptions is that Copilot provides accurate and reliable code suggestions.

What it actually does:

While it can generate useful snippets, the accuracy can be hit-or-miss.

Limitations:

• Frequently suggests outdated practices.
• Sometimes generates insecure or inefficient code.

Our take:

We often find ourselves double-checking Copilot’s suggestions. It’s a time-saver when it works, but it can also lead to more debugging if we’re not vigilant.

Myth 3: It Saves You Time

The idea that Copilot will save you hours of coding is attractive, but the reality might be different.

What it actually does:

It can generate boilerplate code quickly, but the time spent verifying and tweaking its suggestions often negates the time saved.

Limitations:

• Time-consuming to vet suggestions.
• May lead to over-reliance, slowing down your learning process.

Our take:

In our experience, we spend just as much time fine-tuning Copilot’s outputs as we would writing the code ourselves.

Myth 4: It Works Seamlessly with All Languages

Another common belief is that Copilot works well with any programming language.

What it actually does:

While it supports many languages, its effectiveness varies widely.

Limitations:

• Best suited for JavaScript, Python, and TypeScript.
• Struggles with niche or less popular languages.

Our take:

If you're working in a less common language, you might find Copilot underwhelming and frustrating.

Myth 5: It’s Affordable for Everyone

Copilot's pricing model is often overlooked.

Pricing:

• Free tier available.
• Pro version: $10/month.

Limitations:

• The free tier has limited features.
• For serious use, you’ll likely need the Pro version, which adds up over time.

Our take:

At $10/month, it can be worth it if you use it effectively, but it’s an added cost that some indie hackers might want to avoid.

Tool Comparison Table

| Tool | Pricing | Best For | Limitations | Our Verdict | |---------------------|-------------------------|----------------------------------|--------------------------------------|--------------------------------| | GitHub Copilot | Free tier + $10/mo pro | JavaScript, Python, TypeScript | Can suggest incorrect code | Use for boilerplate, verify! | | TabNine | $12/mo, $99/yr | Multi-language support | Less context-aware than Copilot | Great for multiple languages | | Codeium | Free | Beginners needing suggestions | Basic suggestions only | Good for newcomers | | Kite | Free + $19.90/mo pro | Python coding | Limited to Python | Use if focused on Python | | Sourcery | Free + $12/mo pro | Python refactoring | Not great for other languages | Best for Python projects | | Replit | Free tier + $20/mo pro | Collaborative coding | Not as in-depth as Copilot | Good for team projects |

What We Actually Use

After testing various tools, we primarily rely on GitHub Copilot for quick boilerplate code generation, but we also use TabNine for multi-language support and Sourcery for Python refactoring. Each tool has its strengths and weaknesses, but they complement each other well.

Conclusion: Start Here

If you're considering GitHub Copilot, remember that while it can be a helpful tool, it’s not a magic bullet. The myths surrounding it can lead to unrealistic expectations. For indie hackers, it’s crucial to maintain a strong grasp of coding principles and use Copilot as a supplementary tool rather than a crutch.

In our experience, pairing Copilot with other tools like TabNine and Sourcery can provide a more well-rounded coding experience. Ultimately, choose the tools that best fit your workflow and budget.