Counting and Enumeration
Opus: Counts items accurately. Generates exactly N items when asked. Tracks quantities across sections.
Haiku: Stronger than model-card priors suggested. Calibration (2026-07-15, Haiku 4.5): exact-word-count sentence generation hit the target 13/13 times at N = 10–14 — under up to four additional simultaneous constraints — while Sonnet at low effort missed twice on the same battery. The decisive factor was definitional precision: each prompt stated the counting rule explicitly ("a word = any run of letters or apostrophes"). Residual risk concentrates in large N (>15, unmeasured), counting inside long free-form outputs, and prompts that leave the unit of counting ambiguous.
Mitigation: Define the unit of counting exactly, in the prompt. Then, for larger N or count-inside-long-output tasks, structure output so counting is mechanical, not cognitive — and prefer a deterministic post-hoc checker (word counts are free to verify) over prompt scaffolding alone.
For "generate exactly 5 items":
Output format:
1. [item]
2. [item]
3. [item]
4. [item]
5. [item]
Number each item. After writing item 5, stop. Do not continue.For verification tasks ("how many X in the input"):
Step 1: List each X found, one per line.
Step 2: Count the lines from Step 1.
Step 3: Report the count.Avoid asking Haiku to count-and-generate simultaneously. Decompose: first decide WHAT, then ensure the right NUMBER.
For large N (>10), provide the numbered scaffold in the prompt itself and have Haiku fill it in.