← AI Terminology
Instruction Following
Instruction following is a model’s ability to comply with user/system directives — format, constraints, role, and multi-step asks — rather than only continuing text freely.
It is the behavioural product of instruction tuning and alignment.
It is the behavioural product of instruction tuning and alignment.
Why It Matters in AI
Base LMs complete text; products need models that obey. IFEval-style evals and instruction-tuning datasets target this skill specifically. Poor instruction following breaks tools and enterprise workflows.
Key Points
| Aspect | Description |
|---|---|
| Evals | IFEval, Force-follow formats, tool schema tests |
| Measure | Constraint satisfaction rates |
| Product | Core chat quality dimension |
| Related | System prompts, structured outputs, SFT |
| Failures | Ignores constraints; partial compliance |
| Training | SFT on (instruction, response) + preference optim |
Simple Analogy
A sous-chef who actually follows the recipe’s constraints (“no salt”, “plate in a circle”) instead of improvising a different dish.
Common Usage Examples
- IFEval benchmark scores
- SFT on diverse instruction mixtures
- Test: “reply in JSON only” compliance
- Prefer models with strong IF for agents
Summary
In short: Instruction following is reliably obeying directives and constraints — the skill that makes chat models usable as software components.