16 Apr 2025

Prompt Engineering: Your Consulting Edge

4 Steps to Transform AI Outputs From Average to Exceptional

U
Usman SheikhPublished on LinkedIn
Prompt Engineering: Your Consulting Edge

Prompt engineering is the new consulting superpower.

Most haven't realized it yet.

Over the last couple of days, I reviewed the latest guides by Google, Anthropic and OpenAI.

Some of the key recommendations to improve output:

→ Being very specific about expertise levels requested

→ Using structured instructions or meta prompts

→ Explicitly referencing project documents in the prompt

→ Asking the model to "think step by step"

Based on the guides, here are four ways to immediately level up your prompting skill set as a consultant:

  1. Define the expert persona precisely "You're a specialist with 15 years in retail supply chain optimization who has worked with Target and Walmart."

Why it matters: The model draws from deeper technical patterns, not just general concepts.

  1. Structure the deliverable explicitly "Provide 3 key insights, their implications and then support each with data-driven evidence."

Why it matters: This gives me structured material that needs minimal editing.

  1. Set distinctive success parameters "Focus on operational inefficiencies that competitors typically overlook."

Why it matters: You push the model beyond obvious answers to genuine competitive insights.

  1. Establish the decision context "This is for a CEO with a risk-averse investor applying pressure to improve their gross margins."

Why it matters: The recommendations align with stakeholder realities and urgency.

The above were the main takeaways I took from the guides which I found helpful.

When you run these prompts versus generic statements, you will see a massive difference in quality and relevance.

Bonus tips which are working for me:

→ Create prompt templates using the four elements

→ Test different expert personas against the same problem (I regularly use "Senior McKinsey partner" to counter my position detecting gaps in my thinking.)

→ Ask the model to identify contradictions or gaps in the data before finalizing any recommendations.

We're only scratching the surface of what these "intelligence partners" can offer.

Getting better at prompting may be one of the most asymmetric skill opportunities all of us have today.

Share your favourite prompting tip below!

P.S Was this post helpful? Should I share one post per week on how I'm improving my AI-related skills?

U
Usman SheikhPublished on LinkedIn

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