understanding · Article
What “deep AI research” means in practice
Jan 05, 2025
Disclaimer
This content is provided for educational purposes only and does not constitute professional, legal, financial, or technical advice. Results may vary, and you should conduct your own research and consult qualified professionals before making decisions.
Why terminology matters
When we say “deep AI research” on this site, we do not mean only frontier model training or novel architecture work. We use the phrase to refer to any investigation that:
- Produces testable hypotheses about model behavior.
- Connects those hypotheses to measurable outcomes in real workloads.
- Surfaces failure modes and trade-offs instead of only improvements.
This definition is intentionally broad enough to include prompt engineering, evaluation design, and system integration, but narrow enough to exclude marketing-style demos with no instrumentation.
Operator checklist
- Re-run the same task 5–10 times before drawing conclusions.
- Change one variable at a time (prompt, model, tool, or retrieval).
- Record failures explicitly; they are the fastest route to signal.