If you can’t brief AI properly, you’re not getting even 30% of its value.
Whether you’re using GPT-5.1, Gemini 3, Claude Opus 4.1, or any enterprise agent ecosystem, the quality of your instructions determines the intelligence of the output. And as companies roll out agentic workflows, retrieval-augmented systems, and autonomous copilots, “prompting” stops being a gimmick — it becomes a leadership skill.
Every major AI provider now converges on the same principle:
Clear roles, explicit missions, rich context, structured expectations, and self-evaluation produce the highest-quality outputs.
This isn’t magic. It’s simply how high-performing humans work.
And today’s AI behaves the same way.
In this guide, you’ll get:
The updated D.A.R.C.E.E.R. Prompt Formula (V2)
Clear explanations of what each step means
A complete, real-world executive example showing how to apply every step
A final full prompt you can copy-paste into any model today
Let’s dive in.
The New D.A.R.C.E.E.R. Prompt Formula (V2)
Treat every prompt like you’re briefing a top-tier senior consultant joining your team with zero context. Your job is to give them the role, mission, constraints, audience, and deliverable clarity they need to perform at their best.
D – Define the Worker
Give the AI a specific role, seniority, and domain expertise.
This taps into the model’s ability to adopt reasoning patterns aligned with expert personas.
Example roles:
“Senior Strategic Ops Analyst, 15+ years”
“Management consultant specializing in cost transformation”
“Behavioral scientist with experience in org change”
A – Assign the Mission
State exactly what outcome you want — not the activity.
Modern models perform best with mission clarity, not vague brainstorming.
Examples:
“Your mission is to produce a 3-step stabilization plan.”
“Your mission is to rewrite this for my board deck.”
“Your mission is to diagnose root causes and propose actions.”
R – Reveal the Background
Give the model the same context you’d provide a senior consultant.
This is where most execs under-prompt.
Include:
Data
KPIs
Constraints
Risks
Politics
Examples
Time pressure
The richer the context, the richer the reasoning.
C – Clarify the Audience
Tell the model who the output is for — the board, tech teams, regulators, customers, employees, or investors.
The output changes drastically based on audience.
E – Explain Expectations
Define:
Format (bullets, sections, tables)
Length
Tone (executive, simple, persuasive, neutral)
Required elements
This is where you eliminate ambiguity and force structure.
E – Establish Evaluation Criteria
Ask the model to self-check its answer before giving it to you.
This step massively reduces hallucinations and improves quality.
Examples:
“Check for realism and feasibility.”
“Verify alignment with constraints.”
“Ensure consistency across all sections.”
R – Request Refinement
Always ask for a V2.
Iteration is one of the strongest prompting techniques in GPT-5.1, Gemini 3, and Claude Opus 4.1.
Examples:
“Now produce a tighter V2.”
“Rewrite it for executives.”
“Give me 3 alternative strategies.”
Full Walkthrough Example
Scenario: You’re an executive dealing with execution failures and team overwhelm.
Your team of 12 is overloaded. Deadlines are slipping.
Chaos. No headcount available this quarter.
You want AI to act like your Senior Ops Analyst and produce a stabilization plan.
We’ll build the prompt layer by layer using the D.A.R.C.E.E.R. formula.
1. D – Define the Worker
Act as a Senior Strategic Operations Analyst with 15+ years of experience improving execution and workflows in complex organizations.
2. A – Assign the Mission
Your mission is to diagnose why my team is missing deadlines and produce a practical, 3-step action plan that we can implement immediately.
3. R – Reveal the Background
Background:
- Team size: 12 (product, ops, and data)
- Workload: +40% in the last 2 months
- Issues: missed deadlines, low predictability, constant context-switching, Slack overload
- Constraints: no new hires this quarter, limited ability to overhaul processes
- Priority: stabilize execution within 6–8 weeks
4. C – Clarify the Audience
Audience: myself (an executive) and my senior leadership team.
5. E – Explain Expectations
Expectations:
- Tone: direct and executive-friendly
- Max length: 200 words
- Format:
1) Short diagnosis
2) A numbered 3-step action plan
3) 3 key risks to monitor
6. E – Establish Evaluation Criteria
Evaluation:
Before presenting the final answer, verify that your recommendations:
- Respect constraints (no headcount, limited bandwidth)
- Are feasible within 6–8 weeks
- Directly address the root causes
7. R – Request Refinement
Refinement:
1) Produce your best version.
2) Then produce “Action Plan v2” that is shorter, sharper, and simpler while keeping the substance.
Final Combined Prompt (Copy-Paste Ready)
Act as a Senior Strategic Operations Analyst with 15+ years of experience improving execution and workflows in complex organizations.
Your mission is to diagnose why my team is missing deadlines and produce a practical, 3-step action plan that we can implement immediately.
Background:
- Team size: 12 (product, ops, and data)
- Workload: +40% in the last 2 months
- Issues: missed deadlines, low predictability, constant context-switching, Slack overload
- Constraints: no new hires this quarter, limited ability to overhaul processes
- Goal: stabilize execution within 6–8 weeks
Audience: myself (an executive) and my senior leadership team.
Expectations:
- Tone: direct and executive-friendly
- Max length: 200 words
- Format:
1) Short diagnosis
2) Numbered 3-step action plan
3) 3 concrete risks to watch
Evaluation:
Before giving the final answer, check that your recommendations:
- Respect constraints
- Are feasible within 6–8 weeks
- Directly address the defined problems
Refinement:
1) First, draft your best version.
2) Then produce a second version (“Action Plan v2”) that is even tighter and clearer.
Why Executives Must Master This
Prompting is now an executive competency because:
1. Agents need structured instructions
Every enterprise AI roadmap is moving toward agentic systems.
Agents plan, reason, call tools, search, and chain tasks — but they only work as well as the instructions you give them.
2. Risk & hallucinations decrease when prompts are structured
Evaluation and refinement steps reduce errors and improve reliability.
3. Your org’s knowledge will soon be connected to AI
RAG, internal search, and tool-calling require precise directives:
“Use this data. Don’t use that. Apply these policies. Prioritize this.”
4. AI becomes your leverage engine
A good prompt transforms AI into a:
strategy analyst
PM
operations engineer
workflow designer
advisor
researcher
communications partner
Executives who master this get unfair advantage.
Those who don’t… get bottlenecked.
One-Sentence Takeaway
Brief AI the same way you brief your best consultant: role, mission, background, audience, expectations, evaluation, refinement.
That’s D.A.R.C.E.E.R. V2 — and it works on every model you will use in 2025 and beyond.
📩 Reach out to us at [email protected] or book a discovery call to explore partnerships.
Let’s redefine customer experience—faster, smarter, and responsibly—at global scale.
About the Authors
Sam Obeidat is a senior AI strategist, venture builder, and product leader with over 15 years of global experience. He has led AI transformations across 40+ organizations in 12+ sectors, including defense, aerospace, finance, healthcare, and government. As President of World AI X, a global corporate venture studio, Sam works with top executives and domain experts to co-develop high-impact AI use cases, validate them with host partners, and pilot them with investor backing—turning bold ideas into scalable ventures. Under his leadership, World AI X has launched ventures now valued at over $100 million, spanning sectors like defense tech, hedge funds, and education. Sam combines deep technical fluency with real-world execution. He’s built enterprise-grade AI systems from the ground up and developed proprietary frameworks that trigger KPIs, reduce costs, unlock revenue, and turn traditional organizations into AI-native leaders. He’s also the host of the Chief AI Officer (CAIO) Program, an executive training initiative empowering leaders to drive responsible AI transformation at scale.
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