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Human in the loop is a must — but so is proper prompting. That’s why I’m introducing CLEAAR-R: a framework designed for sustainability professionals using AI.
It’s been almost two years since I started Sustainatrend — originally as a way to explore my own questions at the intersection of sustainability, tech, and how we actually get work done. Turns out, those questions weren’t mine alone. This newsletter is for anyone working in the sustainability ecosystem — from corporate to consulting, audit to NGO — who’s trying to stay sharp, efficient, and ahead of the curve.
Today, that curve includes AI. And with that, new risks. A recent $440,000 refund tied to an AI-generated report is just one example of why “how we use AI” matters as much as the fact that we use it. That’s why I’m introducing a prompting framework I use and recommend: CLEAAR-R.
Why We Need a Prompting Framework
AI has quietly become a core part of many sustainability professionals’ workflows — from research to benchmarking, drafting reports to generating ideas. But when the stakes are high, getting the prompt wrong can cost more than just time.
Take the recent case involving Deloitte. The firm agreed to refund AUD 440,000 after errors were found in a report it produced for the Australian government’s compliance framework. The report contained hallucinated references, incorrect citations, and gaps in traceability and logic. This wasn’t an ESG analysis gone wrong — but the mechanisms of failure look dangerously familiar for any sustainability professional relying on AI. The same kinds of hallucinations, misalignments, or missing context could undermine an ESG report just as fast.
That’s where a prompting framework becomes your first line of defense. With structure, clarity, and checks built in, you reduce the risk of rabbit holes, errors, and outputs that look polished but crumble under scrutiny.
When to Use CLEAAR-R (and When Not To)
Let’s be clear: not every prompt requires a complex framework.
For fast, focused tasks — like checking a regulation detail, summarizing a guideline, or brainstorming questions — a lightweight approach works best. That’s where a simple LCA-style structure (Lens, Context, Action — not Life Cycle Assessment!) does the job. I’ll cover this framework in more detail another time.
But CLEAAR-R is built for something different: deep, layered, strategic work.
It’s for sustainability professionals tackling challenges that require not just output — but clarity, alignment, and iteration. Think policy drafts, strategy development, ESG reporting alignment, or multi-stakeholder briefings. In these cases, the prompt becomes more than a single question. It evolves into an ongoing collaboration — a kind of agent you’ll come back to, refine, and build on over time.
That’s when a framework like CLEAAR-R becomes not just helpful — but essential.
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What is CLEAAR-R?
CLEAAR-R is a structured prompting framework tailored for sustainability professionals. It’s designed to reduce ambiguity, prevent AI misfires, and build clarity into every step of your interaction. Whether you're drafting a strategy, reviewing regulations, or benchmarking across frameworks, CLEAAR-R helps you get better outputs — and avoid costly rework or credibility risks.
Here’s how it breaks down:
Element | What It Means | Example in Action |
|---|---|---|
C — Context | Define who the AI should act as, and set the scenario. | “You are an ESG standards expert working in the pharmaceutical industry.” |
| State the specific perspective or role. | “Interpret from the lens of an ESG reporting specialist preparing a CSRD report.” |
E — Expectation | Outline what the output should include (format, structure, tone). | “Break your response into: requirements, key definitions, data typically needed, pitfalls.” |
A — Assets | List the references, documents, or standards to be used. | “Use the ESRS E1 guidance PDF as a reference.” |
A — Assist | Ask for analytical reasoning or insight. | “Compare this draft against ESRS E1 and identify what’s missing.” |
R — Review | Ask the AI to check completeness or reflect before responding. | “Verify all E1-5 sub-points are addressed before finalizing.” |
R — Refine | Invite iteration or follow-up prompts. | “Suggest how I could deepen the second point with relevant industry examples.” |
Each part is designed to help you think through the task clearly — and guide the AI to produce focused, relevant, and usable results.
Final Thought: Frameworks Don’t Replace Judgment
CLEAAR-R isn’t about outsourcing your thinking to AI — it’s about structuring your thinking so AI can support it more effectively. A well-structured prompt won’t eliminate risk entirely, but it reduces it. It won’t write a perfect strategy, but it can speed up the first draft. Most importantly, it helps you work with AI as a trusted copilot, not an unchecked autopilot.
As AI becomes more embedded in how sustainability professionals work, the tools we use — and how we use them — will define our impact. Frameworks like CLEAAR-R are just one way to make sure we stay in control, focused, and aligned.
Closing Note: The ESG Masterclass
For those who don’t know me — I started out as a chemical engineer before deciding to shift careers and step into the ESG field. Like many of you trying to land your first ESG role, the journey was tough. What made it harder was the lack of clear guidance — no blueprint, no roadmap on where to focus or how to build the right skills.
That’s exactly why I created the ESG Masterclass It’s designed to give you the know-how to land your first ESG role, plus the trusted sources you need to keep learning and growing in this fast-changing field.
Over 250 professionals have already joined, and the feedback has been fantastic. If you’re ready to take your ESG career to the next level, you can join now with a 50% discount.
