Las 10 reglas de oro del prompt engineering para modelos de razonamiento en 2026

Modern LLMs are pre-trained extensively on structured XML and Markdown corpora. Segregate instructions, untrusted user inputs, and output constraints using clean XML tags (<context>, <rules>, <constraints>, <output_format>) to prevent context contamination.

Vague stylistic requests produce hallucinations. Define explicit negative boundaries (e.g., forbidding external runtime dependencies or boilerplate introductions) alongside canonical input-output examples.

Deploy this standardized XML prompt template for enterprise-grade code review pipelines.

Allocate token budgets precisely according to task complexity: constrain lightweight classifier tasks to 1,024 thinking tokens, scaling to 16,384 tokens for distributed concurrency debugging.