AI Training
Prompt Engineering and AI Workflow Design
Custom AI workflows for environmental monitoring, policy analysis, and knowledge management, plus team training on responsible use.
The challenge
Prompt Engineering and AI Workflow Design
Most environmental teams know AI could help but have no reliable way to use it — prompts are ad hoc, outputs are unverified, and no one owns governance. The value is in designed workflows and trained people, not one-off cleverness.
How I work
The approach
A field-verified method, not a desk exercise.
01
Map the workflow
Identify where AI genuinely saves time — monitoring triage, literature synthesis, policy scanning, reporting drafts — and where it should not be trusted.
02
Design and test
Build prompt patterns and workflow steps with checks for accuracy, then validate against real cases.
03
Train and hand over
Teach the team the method and leave a governance guide for responsible use.
What you get
Deliverables
Design
Workflow architecture
Documented AI workflows mapped to your real tasks.
Method
Prompt patterns
Reusable, tested prompt structures your team can run.
Governance
Responsible-use guide
Guardrails for accuracy, verification, and when not to use AI.
Training
Team session
Hands-on training and knowledge transfer.
I hold applied credentials in Generative AI and LangChain-based application design, and I build evaluation datasets for frontier models daily. I teach the method I actually practise.
Environmental AI Data Contributor and trainer