Lesson 1702 of 2116
AI tools: how to choose an AI coding assistant for your team
Compare on autonomy level, codebase awareness, license terms, and review fit. The hot tool isn't always the right tool.
Lesson map
What this lesson covers
Learning path
The main moves in order
- 1The premise
- 2tool selection
- 3evaluation criteria
- 4team fit
Concept cluster
Terms to connect while reading
Section 1
The premise
AI coding assistants vary across autonomy (autocomplete vs full-agent), codebase awareness (file vs repo), and licensing (training on your code or not). The choice matters more than which model is underneath.
What AI does well here
- Autocomplete inside the editor with low latency
- Generate larger blocks when given a comment prompt
- Run as agents that edit multiple files when allowed
What AI cannot do
- Tell you which mode fits your team's review culture
- Guarantee your code isn't used for training without contract review
- Replace the architectural judgment of senior engineers
Key terms in this lesson
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