AI Coding Assistants: The Real Comparison After 12 Months

Everyone has opinions about AI coding tools. Few have data.

I’ve tracked usage, productivity, and actual output across our team for 12 months. Here’s the real comparison.

The Contenders

We tested:

  • GitHub Copilot
  • Cursor
  • Codeium
  • Amazon CodeWhisperer
  • Various ChatGPT/Claude workflows

Team size: 8 developers. Mix of senior and junior. Python, TypeScript, React stack.

GitHub Copilot

Cost: $19/month individual, $39/month business

What works:

  • Autocomplete is excellent. Best-in-class for line-by-line suggestions.
  • Low friction. Works in VSCode without thinking about it.
  • Stable. Rarely breaks or slows down.

What doesn’t:

  • Chat feature is mediocre compared to dedicated AI assistants.
  • Struggles with complex, multi-file changes.
  • No real architectural understanding.

Best for: Teams who want reliable autocomplete without workflow changes.

Productivity gain: 15-20% measured in lines of code per hour. (Yes, that’s a flawed metric. Still directionally useful.)

Cursor

Cost: $20/month

What works:

  • Whole-file and multi-file edits are genuinely useful.
  • Context-aware suggestions understand your codebase.
  • The “chat about code” experience is better than Copilot Chat.

What doesn’t:

  • Steeper learning curve. Takes time to learn the right prompts.
  • Sometimes slower than Copilot for simple completions.
  • Occasional bugs and stability issues.

Best for: Teams doing complex refactoring or greenfield development.

Productivity gain: 25-35% for experienced users. 10-15% for beginners (learning curve).

Codeium

Cost: Free for individuals, $12/month for teams

What works:

  • Best free option. Period.
  • Autocomplete quality approaches Copilot.
  • Lower resource usage than alternatives.

What doesn’t:

  • Less intelligent than paid options for complex tasks.
  • Enterprise features are limited.
  • Smaller context window.

Best for: Cost-conscious teams or individuals who want to try AI coding without commitment.

Productivity gain: 10-15%. Less than paid options but free is free.

Amazon CodeWhisperer

Cost: Free for individual use, $19/user/month for professional

What works:

  • Good AWS integration if you’re deep in that ecosystem.
  • Security scanning features are useful.
  • Free tier is genuinely useful.

What doesn’t:

  • General coding suggestions lag behind Copilot/Cursor.
  • Outside AWS, it’s mediocre.
  • Less community and fewer integrations.

Best for: AWS-heavy shops who want security scanning bundled.

Productivity gain: 10-12% general coding. Higher if you’re writing lots of AWS infrastructure.

The Hybrid Approach

What we actually use: Cursor + Copilot together.

Sounds redundant. Here’s why it works:

  • Copilot for fast autocomplete while typing
  • Cursor for complex tasks, refactoring, multi-file changes

Total cost: $39/developer/month. Productivity gain: 30-40%.

The tools complement each other. Copilot is fast and lightweight. Cursor is powerful but heavier.

What Junior vs Senior Developers Say

Junior developers love: Copilot autocomplete. It’s like having a senior dev looking over your shoulder suggesting patterns.

Senior developers love: Cursor’s multi-file capabilities. It handles the tedious refactoring work.

Everyone hates: When AI suggestions are confidently wrong. Trust but verify.

The Metrics That Matter

Forget “lines of code.” Here’s what actually changed:

  1. Time to first working version: Down 30%. AI helps bootstrap faster.

  2. Debug time: Down 20%. “Explain this error” actually works.

  3. Documentation time: Down 50%. AI writes first drafts.

  4. Code review comments: Unchanged. AI doesn’t catch the important stuff.

  5. Production bugs: Unchanged. Don’t trust AI for correctness.

The Honest Advice

For teams not using AI coding tools yet:

  1. Start with Copilot. Lowest friction.
  2. Add Cursor after 3 months if you want more power.
  3. Budget $30-50/developer/month for AI tooling.

For teams already using AI coding tools:

  1. Measure actual productivity, not feelings.
  2. Consider combinations, not just single tools.
  3. Train your team on effective prompting.

The tools are worth it. But they’re augmentation, not replacement. A bad developer with AI tools is still a bad developer.

Invest in training alongside tools.