Technical Writers

AI for documentation, API references, and style compliance

2 Saturdays
Saturday 9am-1:30pm
15 students max

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Course Overview

Week 1: Foundations

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9:00 - 9:15 | Welcome & Orientation

  • Welcome & instructor introductions
  • Course overview & objectives
  • Logistics (breaks, lunch, bathrooms, WiFi)
  • Hybrid format expectations
  • In-person: Participation guidelines
  • Virtual: Camera on/off policy, chat usage
  • Icebreaker: Quick poll
  • What's your documentation focus? (API docs, user guides, knowledge bases, content strategy, etc.)
  • AI experience level (1-10)
  • One AI concern you have about technical writing

9:15 - 9:45 | What is AI?

  • What is AI, really? (demystified)
  • AI is not magic (it's pattern matching)
  • AI vs ML vs LLM (hierarchy)
  • Three types of AI (overview)
  • Predictive
  • Generative
  • Agentic
  • Common misconceptions debunked
  • When AI helps vs. when it doesn't

9:45 - 10:15 | Predictive AI Deep Dive

  • Predictive AI explained (weather forecasting analogy)
  • How it works (simplified - no math!)
  • Real-world examples:
  • Netflix recommendations
  • Spam detection
  • Credit card fraud detection
  • **For YOUR work:**
  • Content gap prediction (what docs are users searching for but not finding?)
  • Documentation freshness scoring (which pages are outdated based on product changes?)
  • Search analytics and intent prediction (what are users really looking for?)
  • Readability scoring and audience-level classification
  • Translation quality estimation

10:15 - 10:45 | Generative AI Deep Dive

  • Generative AI explained (creative AI)
  • How LLMs work (simplified)
  • Training on massive text
  • Pattern recognition
  • Next-word prediction
  • Real-world examples:
  • ChatGPT
  • GitHub Copilot
  • AI writing assistants

10:45 - 11:00 | Setup Verification & Break Prep

Break: 11:00 AM - 11:30 AM

11:30 - 11:40 | Lab 1 Introduction

  • Lab 1 overview: "Your First AI Conversation - Technical Writing Edition"
  • Learning objectives:
  • Chat with AI model about documentation tasks
  • Write effective documentation-focused prompts
  • Understand parameters
  • Recognize hallucinations in standards and specifications
  • Demo: Instructor walkthrough (5 min)
  • Q&A (3 min)
  • Get started!

11:40 - 12:10 | Lab 1: Your First AI Conversation

12:10 - 12:25 | Lab 1 Debrief & Discussion

12:25 - 12:55 | Agentic AI & Introduction to Agents

  • Agentic AI explained
  • Chatbot (passive) vs Agent (active)
  • Example: Writer asking AI for style tips vs AI agent that checks an entire doc set against your style guide
  • Components of an agent:
  • Goal
  • Reasoning
  • Tools
  • Action
  • Result
  • Modern tooling: MCP (Model Context Protocol) for standardized tool integration

12:55 - 1:20 | Prompt Engineering Workshop

1:20 - 1:30 | Week 1 Wrap-Up & Homework

  • Recap: What we learned today
  • Three types of AI
  • How to use Generative AI for documentation tasks
  • Prompt engineering basics
  • Preview: Next Saturday (tease exciting content)
  • Build a documentation RAG system with YOUR style guides
  • Create your first documentation assistant agent
  • Real content operations cost analysis

Between Weeks: Practice & Exploration

Homework

Hands-on exercises to reinforce learning and prepare for Week 2

Support

Office hours, Slack channel, and async help from instructors

Resources

Additional reading materials and video tutorials