Before it
Few-shot prompting worked, but models did not reliably follow a plain instruction.
The problem
A pretrained model completes text; it has no particular reason to do what you ask.
What it introduced
Fine-tune on many tasks phrased as natural-language instructions, then test on held-out task types.
Why it matters
Instruction following turned out to be a learnable skill that generalises. This is the step before RLHF.
What modern models inherit
Instruction tuning as the first stage of every assistant's post-training.
What came next
T0 in parallel, Flan-T5 at scale, and InstructGPT's supervised stage.