Learn AI for work, in order

Step 1Understand what you are working with

1. 1What is generative AI? A plain-English explainer for professionalsGenerative AI explained in plain English: what it is, how it differs from older software, what it does well, where it fails, and real examples from work.8 min
2. 2How large language models work: the mental model you needA non-engineer's mental model of large language models: tokens, prediction, training, context windows, why they hallucinate, and reasoning models.10 min
3. 3AI hallucinations explained: why models make things up and how to catch itWhat AI hallucinations are, why models invent facts, the situations where it happens most, and a verification checklist to run before anything ships.9 min

Step 2Get results on day one

1. 4How to use AI at work: a practical operating manualAn operating manual for using AI at work: pick a tool, learn five daily use cases, prompt well, verify output, protect data, and follow a 30-day plan.11 min
2. 5Prompt engineering guide: how to write prompts that get useful answersLearn the anatomy of a good prompt (role, task, context, format, constraints, examples), how to iterate, and a reusable template you can copy today.11 min
3. 6Prompt frameworks that work: RTF, CO-STAR, CRISPE, and when to use eachA plain comparison of popular prompt frameworks (RTF, CO-STAR, CRISPE, Chain of Density, Persona-Task-Format) with worked examples and a decision table.10 min

Step 3Apply it to real work

1. 7AI for email and writing: draft faster without sounding like a robotHow to draft, reply, rewrite, and tighten emails with AI while keeping your own voice, with good and bad examples and the workplace etiquette rules.10 min
2. 8How to summarize documents with AI: PDFs, transcripts, reports, and email threadsA practical method for summarizing long PDFs, transcripts, reports, and email threads with AI: chunking, structured summaries, and omission checks.10 min
3. 9AI for Excel and spreadsheets: formulas, cleanup, and the never-trust-the-total ruleUse AI to write Excel and Sheets formulas, clean messy data, explain a workbook, and generate Power Query, Apps Script, or VBA, then verify every number.11 min

Step 4Pick and set up your tools

1. 10ChatGPT vs Claude vs Gemini vs Copilot: which AI assistant fits your work?An honest comparison of ChatGPT, Claude, Gemini, and Microsoft Copilot for working professionals: writing, files, research, privacy, and how to choose.10 min
2. 11Best AI tools for work: a curated shortlist by categoryA curated list of AI tools for work by category: chat, writing, meetings, research, slides, automation, data, and coding, plus how to evaluate any tool.10 min
3. 12Custom GPTs vs Claude Projects vs Gemini Gems: how to build a reusable AI assistantWhat custom GPTs, Claude Projects, and Gemini Gems are, when to build one, how to write instructions that hold up, and how to share and govern them.10 min

Step 5Stay safe and credible

1. 13AI privacy at work: what happens to what you pasteWhere your pasted text goes, how consumer and enterprise AI plans differ, a red/yellow/green data test, and how to ask IT for an approved tool.10 min
2. 14How to fact-check AI output: a step-by-step processA step-by-step process for verifying AI-generated facts, numbers, quotes, code, and citations, with prompts that make the model show sources and doubt.10 min
3. 15How to write a team AI policy (with a fill-in template)A manager's step-by-step for a team AI policy: scope, approved tools, data rules, disclosure, verification duties, IP, training, and a fill-in template.10 min

Step 6Turn it into a career advantage

1. 16Automate your workflow with AI: from saved prompts to simple agentsA ladder from saved prompts to Zapier, Make, and n8n automations with an AI step and simple agents, plus when not to automate and how to test safely.10 min
2. 17How to AI-proof your career: a level-headed planWhich tasks AI is likely to absorb, which skills compound in value, how to become the person on your team who knows how to use it, and a 90-day plan.9 min
3. 18How to learn AI skills: a 30/60/90-day roadmap for busy professionalsA self-directed roadmap from zero to fluent with AI at work in 90 days: weekly practice, projects to build, free resources, and how to measure progress.10 min
4. 19How to put AI skills on your resume (and back them up in the interview)Describe AI skills credibly on your resume and LinkedIn: outcome-based bullets, before-and-after examples, interview questions, and what not to claim.9 min

Step 7Master the tool you actually have

1. 20How to use ChatGPT at work: setup, ten workflows, and what to avoidHow to use ChatGPT at work: plan setup, data and memory settings, ten workflows with example prompts, files, custom GPTs, Projects, and voice.10 min
2. 21How to use Claude at work: Projects, artifacts, files, and privacy settingsA practical guide to Claude at work: privacy setup, Projects and knowledge, artifacts for small tools, file analysis, connectors, and example prompts.10 min
3. 22How to use Copilot in Microsoft 365: Word, Excel, PowerPoint, Outlook, and TeamsHow to use Microsoft 365 Copilot at work: Copilot Chat with work grounding, Word, Excel, PowerPoint, Outlook, Teams recaps, agents, and limits.11 min
4. 23How to use Gemini in Google Workspace: Gmail, Docs, Sheets, Slides, and MeetHow to use Gemini in Google Workspace: Gmail, Docs, Sheets, Slides, and Meet, the Gemini app with Workspace grounding, Gems, NotebookLM, and limits.11 min
5. 24How to build a custom GPT: a step-by-step guide with an instruction templateBuild a custom GPT step by step: pick a repeatable task, write instructions from a template, add knowledge files, test edge cases, share, and maintain it.11 min
6. 25AI meeting notes: how to choose a note-taker and get notes you can act onHow to choose an AI note-taker (Otter, Fireflies, Read AI, tl;dv, Zoom, Copilot, Gemini), handle consent, and turn transcripts into notes you can act on.11 min

Step 8Go deeper on real work

1. 26AI for presentations: from outline to slides without the fillerUsing AI for presentations: structure the story, draft slides in Gamma, Copilot, Gemini, or Canva, write speaker notes, tighten the deck, and rehearse.10 min
2. 27AI for project management: status reports, RAID logs, and updates that hold upHow project managers use AI for status reports, RAID logs, follow-ups, stakeholder updates, schedule checks, and retros, and what never to delegate.11 min
3. 28AI for data analysis: get real answers from a CSV without being an analystHow non-analysts use ChatGPT, Claude, Gemini, and Julius to clean, pivot, chart, and sanity-check a CSV, with the traps to avoid and a worked example.11 min
4. 29AI agents at work: what they can do today, where they fail, and how to try one safelyWhat AI agents can actually do at work in 2026, where they fail, how prompt injection works, and how to try one safely with a human in the loop.11 min
5. 30AI and copyright at work: who owns the output and what you can safely useWho owns AI output, where the training-data lawsuits stand, using generated text and images commercially, what indemnification covers, and a checklist.11 min
6. 31AI detectors don't work: what teachers and managers should do insteadWhy AI-writing detectors misfire on honest writers, especially non-native speakers, and what teachers and managers should do instead: process, not scores.10 min

Step 9Lead the change on your team

1. 32How to talk to your boss about AI: making the case for a tool, budget, or pilotPitch an AI tool, budget, or pilot to your boss: frame the ask around one task, answer security, cost, quality, and jobs objections, and use the template.10 min
2. 33How to run an AI pilot: a manager's plan from two workflows to a decisionA manager's step-by-step AI pilot plan: pick two workflows, set a baseline, choose tools and data rules, train five people, measure two weeks, decide.11 min
3. 34How to measure AI ROI without fooling yourselfHow to measure AI ROI honestly: time saved, quality, cycle time, cost, and error rates, with a simple worksheet and a one-page readout for leadership.11 min
4. 35AI for small business: where to start when you have no IT departmentThe five highest-value AI uses for a small business, which tools to pick, customer-privacy basics, a 30-day plan, and what it all costs in general terms.11 min

PracticeUse the free tools as you go

Eight terms to know first

• Large language model (LLM)A large language model (LLM) is a neural network trained on enormous amounts of text to predict the next word, then tuned to follow instructions and hold a conversation. LLMs power ChatGPT, Claude, Gemini, and Microsoft Copilot.
• PromptA prompt is the text (and sometimes files or images) you give an AI model to tell it what you want. A good prompt states the role the AI should play, the task, the relevant context, the output format, and any constraints.
• TokenA token is the unit of text a language model reads and writes, usually a word or a piece of a word. Models measure input limits, output limits, and pricing in tokens; as a rough rule, 1,000 tokens is about 750 words of English.
• Context windowThe context window is the maximum amount of text, measured in tokens, that a language model can consider at one time. It includes your prompt, any pasted documents, the conversation so far, and the model's reply.
• HallucinationA hallucination is when an AI model produces information that is false or fabricated but presents it confidently, such as an invented statistic, a citation to a paper that does not exist, or a made-up product feature.
• AI agentAn AI agent is a system that uses an AI model to pursue a goal on its own by planning steps, using tools such as web browsers, files, and software APIs, and adjusting based on results, rather than answering a single prompt.
• Retrieval-augmented generation (RAG)Retrieval-augmented generation (RAG) is a technique in which an AI system first searches a set of documents for relevant passages and then gives those passages to a language model to answer from. It lets an assistant use your own, current information.
• Prompt injectionPrompt injection is an attack in which instructions hidden inside content an AI system reads, such as a web page, email, or document, hijack the system into doing something its user never asked for.