AI Coding Tool Breakdown - AI Copilots vs AI Coding Assistants vs AI Software Engineers
AI Summary
Summary: AI Coding Tools Breakdown
Categories of AI Coding Tools:
- AI Co-Pilots (Tier 1)
- Basic level tools known as AI autocompletes.
- Examples: GitHub Co-pilot, Super Maven, Cursors Co-pilot Plus+.
- AI Coding Assistants (Tier 2)
- Superset of AI Co-pilots with superior capabilities.
- Examples: Cursor AER, Continue.
- AI Software Engineers (Tier 3)
- Highest level with full autonomy, potentially making other tools obsolete.
- Examples: Open Devon, Co-pilot Workspace.
- Still immature and not widely recommended.
Increasing AI Autonomy:
- Each level up decreases the manual work required by engineers.
- AI autonomy increases from Co-pilots to Software Engineers.
Key Features of AI Coding Assistants:
- Selection Prompt: Modify code by highlighting and prompting changes.
- Selection Prompt with Context: Modify documentation with context from other files.
- Terminal Prompt with Context: Generate terminal commands based on documentation.
- Chat Prompt with Context: Ask questions about the codebase for quick refresher.
- Web Search: Use external documentation to answer coding questions.
Recommendations:
- Always have an AI Co-pilot running.
- Primarily use an AI Coding Assistant for productivity.
- Embrace AI tools to avoid falling behind in productivity.
Future of AI in Coding:
- AI Software Engineers promise end-to-end task prompting.
- Transition to AI tools is crucial for staying competitive in the field.
Conclusion:
- AI Coding Assistants are currently the best tool for coding.
- Engineers using AI tools will outpace those who don’t.
- Upcoming resources will help engineers adapt and evolve with AI advancements.