Software Engineering

Code Assistant AI Architecture

Compare RAG, fine-tuning, long-context, and hybrid approaches for code assistant at 200K queries/month.

Top approaches

#1 Best fit

Fine-Tuning

Proprietary codebase style and APIs require domain adaptation.

#2 Runner-up

RAG

Works well for doc retrieval but lags on style and API knowledge.

#3 Alternative

Hybrid / RAFT

Best accuracy but highest ops burden.

Estimated at 200K queries/month

Long-Context$4,044/mo

RAG$5,622/mo

Fine-Tuning$7,381/mo

Hybrid / RAFT$10,050/mo

1Training data quality matters more than quantity — curate 10 K high-quality function-docstring pairs.
2Evaluate on held-out PRs, not on training-set files.
3Re-train quarterly when major internal library versions are released.

Code Assistantのデフォルトで事前入力された9つの質問に答えて、決定論的なアーキテクチャ推奨、コスト・クロスオーバー・チャート、8ページのPDFレポートを取得してください。