For automation engineers who want to safely use AI agents in their PLC workflows.
You don't need to become a machine learning expert. You don't need to understand transformers or neural networks. You need to know how to safely prompt an LLM, structure its outputs, and constrain its behavior.
This track teaches you to USE agentic AI the way you use a PLC: with clear inputs, predictable outputs, and absolute control.
110% complete
Complete all 10 tutorials to gain full control over agentic AI in your industrial workflows. Start with T0 if you need Python basics.
Configure Your AI Workbench in 20 Minutes
Set up your OpenAI API access safely and correctly. Get your API key, configure your environment, and make your first test call in 20 minutes.
The Only Python You Need to Safely Use Agentic AI as a PLC Engineer
Learn the minimal Python needed for industrial AI. Variables, loops, conditions - nothing more. Ready in 45 minutes.
From Deterministic Control to Reasoning Under Uncertainty
Learn the fundamental difference between traditional automation and agentic AI. From execution to reasoning.
From Static PLC Code to Transparent, Step-by-Step Machine Reasoning
Apply ReAct reasoning to PLC code analysis. Learn transparent, auditable AI reasoning for industrial automation.
What Actually Makes Something an Agent in Industrial Automation?
Distinguish rule-based automation from autonomous agents. Goals, state, and reasoning make the difference.
How Memory Transforms Stateless LLM Calls into Context-Aware Reasoning
Learn how conversation memory enables agents to detect patterns across observations and maintain context for industrial diagnostics.
How to Control AI So It Generates Consistent, Read-Only PLC Code Drafts
Control AI code generation with prompt engineering. Create reviewable, consistent PLC code drafts safely.
Teaching AI What Good Looks Like Using Curated PLC Examples
Learn how to guide AI toward consistent and reliable PLC code validation by supplying high-quality examples --- without giving it control.
Making AI Show Its Work on IEC 61131-3 ST
Learn how to get AI to explain its reasoning step-by-step when reviewing PLC logic, improving clarity, trust, and debuggability.
Connecting Reasoning to a Single Read-Only Tool
Learn how to safely connect an AI agent to a single, read-only tool to analyze PLC logic without any control authority.
From Free-Text Reasoning to Machine-Readable Results
Learn how to force AI agents to return deterministic, structured outputs when analyzing PLC logic, enabling reliable downstream processing.
An Extensible Advisory Agent with Multiple Read-Only Tools
Build a professional, end-to-end advisory diagnostic agent that analyzes conveyor alarm logs and correlates them with known fault patterns.
Begin with Tutorial T0 if you need Python basics, or jump straight to Tutorial 1 to learn the difference between traditional automation and agentic AI.