Master advanced prompting: the 2026 guide

Why basic prompting isn''t enough anymore

In 2026, knowing how to write "Make me an email for my customer" no longer sets anyone apart. Every tool can handle simple prompts. What makes the difference today is the ability to orchestrate a model: chain steps, give examples, have it critique its own work.

Here are the 5 advanced prompting techniques every pro should master.

1. Chain-of-thought (CoT)

Instead of asking for the answer, ask for the reasoning.

Bad: "What''s the best channel to sell to SMBs?"

Good: "Before answering, list the criteria for evaluating a sales channel (cost, scalability, cycle time...). Then apply them to 4 candidate channels. End with your recommendation."

This structure forces the model to reason step by step. Hallucinations drop, quality rises.

2. Few-shot prompting

Giving 2 or 3 examples of the expected output is worth a thousand adjectives.

Here are 2 article titles that work for our audience:
— "The classic trap 80% of B2B salespeople fall into"
— "3 mistakes that ruin your email follow-ups"

In the same style, suggest 10 titles for an article on [topic].

The model copies the tone, length, structure — without you having to describe them.

3. Task decomposition

One big request = bad answer. Break it down:

1. "List the sections of a white paper on [topic]."
2. "For section 2, give me 5 main ideas."
3. "Write section 2, idea by idea, 200 words each."

You keep control at each step, and overall quality is much better than with a mega-prompt.

4. Structured role priming

"You are an expert in X" has become a cliché. Better:

You are [role].
Your experience: [10 years in..., specific context].
Your style: [direct, educational, factual].
Your constraints: [never do X, always do Y].
Your task: [task].

The more the role is framed, the more calibrated the answer.

5. Self-critique

Ask the model to grade and improve its own work:

Here''s your previous answer. Grade it out of 10 on these criteria: accuracy, structure, originality. Then suggest an improved version that fixes the weakest points.

Surprisingly effective: the second version is almost always better than the first.

Combine the techniques

Pros chain: role priming → few-shot → chain-of-thought → self-critique. This turns a generic assistant into a specialized collaborator.

The trap: overload

Too many techniques kill the techniques. If your prompt is 3 pages long and the result is worse than with a simple version, it''s become unreadable for the model. Aim for precision, not verbosity.

Going further

Our Formation IA Adulte training dedicates an entire module to advanced prompting, with an AI coach that critiques your prompts in real time and helps you progress exercise after exercise.