AI Agents for Climate
Most climate professionals are still using AI as a question-answering tool. Agents are different: you define the goal, the system executes. This course covers what that shift actually means — technically, practically, and for high-stakes climate decisions where getting it wrong has consequences.
Start course →What you'll leave with
- ✓Explain what an AI agent is and how it differs from a prompt-response tool
- ✓Design a multi-step agentic workflow with appropriate human checkpoints
- ✓Evaluate when Claude Code or a monitoring agent is the right tool for a climate task
- ✓Build a deployment-ready blueprint for an agent in your own climate work
Course sections
What AI Agents Actually Are
The shift from tool to agent: anatomy, tool use, the oversight imperative, and why climate work specifically needs systems that can pursue goals, not just answer questions.
Designing Agentic Workflows
Workflow MapperHow to decide if a task is agent-worthy, map the steps, identify tool needs, and build human checkpoints. Climate workflow patterns: monitoring, research synthesis, reporting automation.
Claude Code for Climate Work
Copyable promptWhat Claude Code actually is and what it's good at: scaffolding data pipelines, writing analysis scripts, automating file tasks. Plus a ready-to-use climate data pipeline prompt.
Autonomous Monitoring for Climate
What climate monitoring agents look like in practice — deforestation, methane, emissions compliance. The alert design problem, human-AI handoffs, and the MRV question.
Your Agent Blueprint
Agent Blueprint BuilderHow to decide if a task needs an agent. The minimal viable agent principle. Build a structured blueprint for an agent you could actually deploy.