If you’re reading this, you’re likely working in a field I call 'Trying your best to make an impact.'
Most days, that feels incredible. But let’s be real—some days, the imposter syndrome hits hard. You start questioning if your work actually moves the needle. This is especially true if you’re in a large organization; it’s easy to feel like a tiny gear in a massive machine, where your individual contribution feels invisible.
I’m opening with this because I felt exactly like that just last week. If you’re feeling it too, I want you to shift your focus.
The greatest impact doesn't always come from a single line of code or a sustainability report. It comes from empowering those around you. You are one person, but when you develop and inspire your team, your impact multiplies.
If you’re feeling a bit stuck or losing your spark lately, hit reply and share your thoughts. Sometimes we just need an ear from someone who’s been in the trenches. I’ve got you. 😉
Why GPT "Fails" at Sustainability (and how I’m fixing it)
It isn’t just a catchy title to get you to click. it’s the reality I’ve been navigating for the last months.
We often talk about AI as a magic wand, but if you’ve tried to use a generic LLM for complex sustainability tasks, you’ve likely felt that gap between 'The AI hype' and 'real-world use cases.' To close that gap, I’ve started putting my work through what I call a Workflow Audit.
Going forward, this is how I’ll be building—and sharing—every use case with you.
What is a Workflow Audit? It’s a deliberate process to modernize how I work. Instead of just throwing AI at a problem, I deconstruct the task to see what can be enhanced and what needs to be protected. Here is my 4-step breakdown:
Identify or select the task to be audited: Simply identify one task define what is start and what is done means. Boundaries are important.
Mapping the Journey: I draw the process from the moment I decide to start a task until the final output is delivered. A clear step by step workflow.
The "Delete or Delegate" Filter: I look for steps that are redundant or time-consuming. Since I lead a 'team of one' (myself!) ;) I can only delegate to AI.
The Responsibility Anchor: I identify where I must stay in control. In sustainability, accuracy and ethics aren't optional; they require a human in the loop.
By identifying these steps, I can ensure I’m not just using AI for the sake of it, but actually optimizing my impact.
The First Case Study: Mastering Regulations To show you this in action, I applied the audit to one of our biggest headaches: Regulations. I’ve just released a video on how I use NotebookLM to ingest, understand, and explain complex regulatory frameworks in minutes.
In this use case, I take ESPR new directive and simply go through each step I usually perform manually to understand a regulation or any changes in directives, but this time, instead of attaching it to ChatGPT or Gemini, I did go through each step and tried to understand how I make my decisions and what can be delegated and where I really need to make decisions. Check it out it is a really helpful use case Link.
If you work with regulations and directives, this is a gold mine for you!
Have a nice week, until next week.