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.

Cost at typical volume

Estimated at 200K queries/month

Long-Context$4,044/mo
RAG$5,622/mo
Fine-Tuning$7,381/mo
Hybrid / RAFT$10,050/mo

Key considerations

  • 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.

Frequently asked questions

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