AI Coding Agents
What are the best AI coding agents you need to be leveraging now.
Purpose
Those that can leverage AI coding agents to write code that is effective for it's intended purpose have a significant advantage. The key is to create and index of coding tasks and then establish the balance of strengths between human and AI agents.
Problems
Common problems with AI coding agents:
- Next Action Prediction
- Multi-File Edits
- Multi-hop Context
- Bug Detection and Debugging
See Cursor Problems
Agent Types
AI Copilots
AI Coding Assistants
AI Engineers
Practices
The key ingredients to success:
- Choose the right tools to constrain agent behavior
- Using a reactive DAG to allow humans to course-correct agent plans
- Building granular, user-centric evaluators instead of chasing one "god metric"
- Gating releases on the metrics that matter, not just gaming a score
- Constantly scrutinizing model inputs & outputs to uncover insights
Performance
Quality Assessment Benchmarks:
Examples
Useful examples of AI coding agents in action: