Most ESG prompts stumble in familiar ways—same errors, shallow setup. Quality in, quality out.

Prompting isn’t magic; it’s disciplined communication.

An 8-minute, no-fluff read that shows you how to prompt for real results:

Why it fails
When the model must guess your standard (ESRS/GRI/ISO 14001), audience (Board, regulator, customers), industry/site boundary, or systems of record (SAP/ERP/LIMS), it produces diluted, generic outputs. Typical failure modes: wrong clause mapping, irrelevant KPIs, missing evidence, and the wrong tone for the stakeholder.

Quick fix
State the context explicitly (Industry/Site/Location, Standard & Scope/Boundary, Audience / Use case, Stakeholder engaged.

Before
Analyze this report.

After (CSRD example)
Act as a sustainability manager preparing a CSRD compliance note. Analyze this report against ESRS E1 and summarize 5 key gaps with references to relevant clauses.

That’s precisely the challenge our AI × ESG agent is built to solve: a clear, time-saving answer to a confusing regulation.

Why it fails
“Good” isn’t defined. What are you looking for in the output to consider it a success. If you don’t know, most probably AI won’t know.

Quick fix
State success + acceptance tests.

Before:
Write about Scope 3.

After:
Write a 700-word explainer for plant managers on Cat 1 (Purchased Goods & Services): activity data to collect, preferred method (average-data; fallback spend-based), two credible EF sources, and one KPI. Acceptance: includes a data table, sources, and a 1-line implication for Procurement.

Why it fails:
Vague questions (“What is…?”, “How to…?”, “Why…?”) → generic answers.

Quick fix:
Assign the model with clear job with clear deliverables.

Before:
What is double materiality?

After:
You are an ESG advisor. Create a one-page training explainer for finance teams on double materiality under CSRD, with definition, why it matters, and 3 business examples.

Why it fails:
Every prompt has a capacity. When you cram in multiple tasks, the model thins its focus and defaults to shallow, generic output.

Quick fix:
Break the work into a short chain of prompts. Start broad (diagnose), then sequence into planning and comms—passing each output to the next step.

Before:
“Write a gap analysis, roadmap, risk register, and stakeholder plan for CSRD compliance.”

After:

Why it fails:
It sounds trivial, but the role you assign sets the standards, stance, and scrutiny. Without it, you get generic, middle-of-the-road output.

Quick fix:
State the expert, the stance (auditor/skeptic/coach), and the success lens (what “good” looks like).

Before:
Draft an environmental policy.

After:
You are an ISO 14001 lead auditor with a critical eye. Draft an environmental policy designed to pass ISO 14001:2015 Clause 5.2. Include: scope, commitments (compliance obligations, prevention of pollution, continual improvement), framework for objectives, responsibilities, and monitoring approach. Keep it one page, plain language, board-approvable. Flag any clause gaps you see.

Why it fails:
Without gold-standard examples or authoritative sources, the model can’t match tone/density or choose the right data—so you get vague or incorrect output.

Quick fix:
Provide exemplars and tell it where to look.

Before:
Make an emissions reduction plan.

After:
Using SBTi guidance as a reference, draft a Scope 1 & 2 emissions reduction plan for a manufacturing site. Include baseline year, target %, and monitoring KPIs.

How Did Papaya Slash Support Costs Without Adding Headcount?

When Papaya saw support tickets surge, they faced a tough choice: hire more agents or risk slower service. Instead, they found a third option—one that scaled their support without scaling their team.

The secret? An AI-powered support agent from Maven AGI that started resolving customer inquiries on day one.

With Maven AGI, Papaya now handles 90% of inquiries automatically - cutting costs in half while improving response times and customer satisfaction. No more rigid decision trees. No more endless manual upkeep. Just fast, accurate answers at scale.

The best part? Their human team is free to focus on the complex, high-value issues that matter most.

👉 Curious how they did it? Read the full case study to learn how Papaya transformed their customer support

Meet the EUDR Agent

Think of this as your digital compliance consultant. The EUDR Agent is designed to tackle that very first roadblock: figuring out whether the regulation applies to your company, and what comes next.

In seconds, the agent can:

It’s built specifically for teams working with Annex I commodities — coffee, cocoa, soy, palm oil, wood, cattle, and rubber — where misinterpretation could mean costly delays or penalties.

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 200 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.