Prompting better: how language models work.

Good results start with a clear task. Five rules that make the difference in everyday work.

A quick look at the technology

Modern language models are based on the transformer architecture, introduced in 2017. They process text as tokens and calculate the most probable continuation from the context. The model does not "understand" like a human, but it recognises patterns extremely well.

Five rules for better results

• Task, context, format: state what, what for and in which form.
• Give examples: one good example works better than three explanations.
• Step by step: request intermediate steps for complex tasks.
• Set a role: a clear role sharpens tone and depth.
• Iterate: the first answer is a draft, not the result.

From vague to concrete

Instead of "summarise this", try: "Summarise the five most important points as bullet points of at most twelve words each, audience: executive team." The clearer the goal and format, the less rework.

Know the limits

The context window limits how much text the model considers at once. Knowledge may be outdated, and without sources, verification remains a human task.

Prompting is not a magic formula, it is precise briefing.

Conclusion

Anyone who describes task, context and format clearly gets better results, and saves time on rework.