AI at Work 101: Using AI and AI Automation in Your Business
Six practical lessons on putting AI to work in a real business: what language models can and cannot do, how to write prompts that give reliable results, where AI belongs inside a workflow, and how to keep it accurate and safe.
Lessons
- 1How AI language models work (just enough to use them well)What large language models are, how they generate text, what tokens and context windows are, and what that means for what AI is good and bad at in business.
- 2Writing prompts that get reliable resultsA simple five-part structure for business prompts, how to get consistent formats like JSON, using examples, and how to test and improve a prompt.
- 3Where AI fits inside a workflowThe five jobs AI does best inside business workflows, how to combine AI steps with rule-based automation and human review, and three worked examples.
- 4AI agents: goals, tools, and guardrailsWhat AI agents are, how they differ from workflows and chatbots, where they work well in a small business, and the guardrails every agent needs.
- 5Data, privacy, and accuracyHow to use AI at work without exposing customer data or publishing mistakes: approved tools, data minimization, grounding, review steps, and a simple AI use policy.
- 6Planning your first AI automationA step-by-step plan for your first AI automation project: choosing the task, defining success, designing the workflow, piloting with human review, and scaling.
About this course
Is this AI course free?
Yes. All six lessons are free with no sign-up, and your progress is saved in your browser.
Do I need to know how to code?
No. The course is written for business owners and teams. It explains how AI works at the level you need to use it well, and shows how no-code automation tools can run AI steps for you.
Should I take Automation 101 first?
It helps but is not required. Automation 101 explains triggers, actions, and how apps connect, which makes lesson three of this course easier to follow.
Which AI tools does the course use?
The lessons are tool-neutral. The techniques apply to the major AI assistants and model APIs, and to automation platforms such as Zapier, Make, n8n, and Power Automate that can call them.
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