Lesson 511 of 2116
Switching Prompts From GPT/Claude To ABAB — Gotchas
Moving a prompt library to MiniMax-class models is rarely a copy-paste. Five common gotchas — and the patterns that fix them.
Lesson map
What this lesson covers
Learning path
The main moves in order
- 1Same-shape, different-tuned
- 2prompt migration
- 3instruction style
- 4system prompt
Concept cluster
Terms to connect while reading
Section 1
Same-shape, different-tuned
ABAB and Western frontier models all accept system prompts, user messages, and tool definitions. The shape is similar. What differs is which phrasings the model handles best, how strict it is about format adherence, and which few-shot patterns it learns from.
Five common gotchas
- 1Long unstructured system prompts work less well than short structured ones
- 2Negative instructions ('do not include X') sometimes need to be reframed positively
- 3Few-shot examples written in English-only sometimes underperform when mixed with the target language
- 4Tool-call schemas may use slightly different formats than OpenAI's
- 5Strict JSON-only outputs may need explicit reinforcement at the end of the prompt
Compare the options
| Pattern that works on | Western frontier | ABAB |
|---|---|---|
| 3000-token system prompt | Tolerated | Trim and structure first |
| 'Do not include X' | Usually fine | Better as 'Include only Y' |
| English-only few-shots for Chinese task | Mixed | Use Chinese few-shots |
| OpenAI tool schema | Native | Adapt schema syntax |
| End-of-prompt JSON reminder | Helps a little | Often necessary |
Applied exercise
- 1Pick one endpoint to migrate
- 2Build the 30-prompt eval set with known-good outputs
- 3Migrate behind a flag with the gotchas above as your checklist
- 4Roll out 10 percent traffic and watch metrics for a week before fully cutting over
Key terms in this lesson
The big idea: prompts are not portable by accident. Plan the migration, watch the metrics, and the cutover is boring — exactly what you want.
End-of-lesson quiz
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