ChatGPT and AI Assistants

Compare the major assistants, set up accounts, and learn the interface features that matter.

• How ChatGPT, Claude, Gemini, and Copilot differ in practice
• Free versus paid tiers and what free access typically covers
• Conversations, projects or folders, and memory or custom instructions
• Uploading files and images and what the tool can read
• Account privacy settings and data-use controls
• A first conversation: setting goals and expectations

Hands-on lab: Set up two assistants, adjust privacy settings, and run the same starter task in both, noting differences in tone, depth, and accuracy.

Use assistants and search-grounded tools for research while keeping sources visible and checked.

• Breaking a broad question into researchable sub-questions
• Assistants with web search versus assistants without it
• Using Perplexity and Gemini for answers with citations
• Opening and checking cited sources yourself
• Spotting fabricated references and outdated information
• Recording sources in a simple research log

Hands-on lab: Research a topic from your field using two tools, verify five claims against original sources, and log which claims were wrong or unsupported.

Draft and refine emails, reports, and plans while keeping your own voice and accountability.

• Drafting from bullet points and rough notes
• Rewriting for tone, audience, and reading level
• Condensing long text into briefs and action lists
• Giving the assistant a sample of your style
• Fact and tone review before sending
• Disclosure norms when AI helps with writing

Hands-on lab: Turn a real set of notes into a professional email and a one-page summary, edit them for accuracy and voice, and compare versions with a peer.

Use assistants to structure plans, compare options, and surface risks without outsourcing judgment.

• Turning a goal into a milestone and task plan
• Generating options and weighing pros and cons
• Pre-mortems: asking the assistant to find what could go wrong
• Checklists, schedules, and project outlines
• Recognizing when the assistant is agreeing too easily
• Keeping the final decision with a named human owner

Hands-on lab: Build a four-week plan for a real project, run a pre-mortem with the assistant, and revise the plan with at least three changes you can justify.

Analyze documents and simple spreadsheets with assistants and confirm the results yourself.

• Summarizing long documents and extracting key points
• Asking questions of your own sources in NotebookLM
• Cleaning and describing small anonymized tables
• Explaining trends and building simple charts with assistant help
• Recalculating results in Google Sheets to check the assistant
• Removing personal and confidential data before upload

Hands-on lab: Anonymize a small spreadsheet, ask an assistant for three insights, and verify each insight with a formula or manual check in Google Sheets.

Package what works into reusable prompts and instructions, and lock in safe habits.

• Saving prompt templates and custom instructions
• Building a personal prompt library by task type
• A privacy checklist: what never to paste into an assistant
• Organization policies and acceptable-use rules
• Bias and fairness checks on drafted content
• Deciding when not to use an assistant

Hands-on lab: Create five reusable prompts for your recurring tasks, test each on fresh input, and write the review step that goes with each.