AI Curriculum
Learn AI so you don't lose the job. Foundations, then the tools on your desk, then prompts, then the weekly grind.
🌱Beginner
What the word means at a desk, which two tools to open, and a prompt you can run on real work.
What people mean by AI when they talk about your job
A plain map of the tools already sitting in your inbox, docs, and browser — and why “AI” is not a department you wait for.
How AI Actually Works: Autocomplete on Steroids
No jargon, no math, no PhD required. Learn what a large language model really does under the hood - and why it's both impressive and slightly dumb.
The AI Glossary: Speak Robot Without a Translator
LLM, token, RAG, fine-tuning, agent... AI people love acronyms. Here's the 15 terms that actually matter, in plain English, with zero shame attached.
Why the person who uses AI gets the next assignment
A calm look at what changes when one person on the team drafts with AI and another person still starts from a blank page.
What AI Can't Do: A Healthy Skeptic's Guide
AI is brilliant and also profoundly limited. A friendly field guide to the things it gets wrong, so you can use it without being burned by it.
AI Safety & Privacy: What Not to Share With the Robots
Before you paste your whole life into a chatbot, read this. A plain-English guide to protecting your data, spotting AI scams, and staying safe in the age of convincing fakes.
Spotting AI Content: Deepfakes, Bots & Baloney
AI can write, speak, and appear on camera as almost anyone. Here's how to tell what's real, what's generated, and when to verify before you believe.
Two tools for work. That is enough this month.
Pick a general chatbot and the AI already inside the software you use. Ignore the buffet until a real task blocks you.
AI for Everyday Life: Email, Docs & Research
You don't need a business case to use AI. Ten concrete ways to use it today for email, documents, research, and the thousand small tasks that eat your week.
A saved prompt for the job you already have
Custom GPTs and Claude Projects are sticky notes with instructions — not a product company. Pack the voice and fences you reuse every week.
Make the slide image without a designer on call
When your job needs a diagram or a header and design is in another building. Honest limits: hands, logos, and “this looks like a real photo of our CEO.”
Ask the spreadsheet a question you can recompute
Plain-language questions against a file you cleaned. Recompute the total yourself. No “insights you might be missing” fortune-telling.
Write a work prompt the way you write a ticket
Role, facts, fences, and what “done” looks like. The same discipline as a ticket — because a vague prompt is how you get a vague draft with your name on it.
Pick one daily task and stop doing it from scratch
For people with a day job — not a bakery pitch deck. Find a repeatable task, write a prompt, and keep a human on the send button.
Draft the post. You still hit publish.
If your job includes social, use AI for the first pass and the calendar sketch — not for invented customers or fake engagement math.
Use AI on the pipeline without inventing the prospect
For people who already sell. Research and first-line drafts from facts you have — not a lead-gen agency kit.
The draft that will get you in trouble
Hallucinations, privacy, and the verification loop for work you will put your name on. No ethics TED talk.
AI and Your Job: Stay Employed, Stay Relevant
Will AI take your job? Probably not - but someone who uses AI well might take the promotion. A calm, practical guide to staying relevant without the panic.
How we talk about AI here (no fake proof)
The house rule for claims on this site and in your own work: specific, checkable, no borrowed stars.
Understanding Large Language Models (LLMs)
A beginner-friendly introduction to Large Language Models (LLMs), explaining what they are, how they work, and their common applications in a clear and accessible manner.
Your First AI Conversation: A Beginner's Guide
Learn how to initiate and navigate your first conversation with an AI, covering essential tips for effective and meaningful interaction.
Understanding Artificial Intelligence Terminology
Demystify the core concepts and jargon of Artificial Intelligence, from machine learning to deep learning and neural networks.
Write a lesson you could run at your desk tomorrow
The content standard for this school: specific job titles, no slogan fluff, no banned hype words, no fake proof.
The tool cards we actually keep current
A short guide to the /tools catalog: how to use a card at work, then get back to your job.
Triage the inbox. You still send the email.
Sort, summarize, draft. No auto-reply to customers from a consumer model. For people who live in a queue.
Choosing the Right AI Tool for the Job
Learn a simple framework to pick the best AI tool – chatbot, agent, or automation – for your specific business need.
Streamlining Your Meetings with AI Notetakers: An Efficient Workflow
Discover how to integrate AI notetakers into your workflow to save time, improve accuracy, and ensure you never miss a crucial detail from your meetings.
Meeting Prep and Follow-Up with AI
Briefs before, notes during, and action items after every meeting.
Turning Spreadsheets into Insights with AI
Ask plain-language questions of your data and get charts and summaries.
RAG Knowledge Base Basics
An introduction to Retrieval Augmented Generation (RAG) knowledge bases, explaining their core components, benefits, and how they enhance AI models.
Speeding Up Content Creation with AI
A repeatable draft-edit-polish loop for faster publishing.
AI for Research and Summarising Long Documents
Extract the key points from reports, contracts, and articles quickly.
AI, ML, and DL: A Clarified Understanding
Demystify the concepts of Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL). Understand their relationships, core principles, and practical applications, moving beyond hype to a clear, grounded perspective.
Using AI to Write Better Emails Fast
Turn rough notes into clear, on-tone emails in seconds.
When Not to Use AI
A decision rule for skipping the model: high cost of being wrong, no source of truth, one-off work, and jobs where a fluent draft makes you worse.
Data Hygiene Before You Paste Anything Into a Model
A pre-paste checklist: what is a secret, what is someone else's data, what the vendor may train on, and how to redact without wrecking the task.
⚙️Intermediate
Prompts that survive a manager, plus email, meetings, and the queue — with you still on send.
Draft the reply. A person still owns the customer.
If your job is the queue: first-line drafts from an approved library. Not a 24/7 SMB chatbot storefront.
A video draft for the update, not a production studio
When your job needs a short clip or a voiceover scratch track. Honest limits, no “no camera required” agency pitch.
Ask for a script you can read before you run
If your job is not engineering: small scripts and formulas for files you own. Not “build a website and a product this weekend.”
Chat with the policy PDF, not with vibes
RAG in desk language: retrieve a few passages, answer from those, say NEED when the binder is silent. You do not need to become a vector-database vendor.
A checklist with a model in the middle is not an agent company
Chatbot vs checklist vs loop — so you can follow the meeting without volunteering to build a product.
Redact first. Then let the model see the columns.
Prepare a file for a question at work: drop secrets, keep the columns the question needs, write a legend that does not travel.
Content Marketing with AI: From Strategy to Publication
Build a complete AI-assisted content marketing engine - research, draft, edit, and publish consistently without burning out.
Open vs. Closed AI Models: Understanding the Differences
An in-depth look at the distinctions between open and closed Artificial Intelligence models, exploring their development, accessibility, and implications.
AI Email Accelerator: From Notes to Polished Emails Efficiently
Learn how to leverage AI to transform your rough notes into polished, on-tone emails, significantly reducing writing time and effort. This lesson explores practical strategies and best practices for using AI email assistants effectively.
Fine-Tuning vs RAG: A Comprehensive Guide
This guide explores the nuances of fine-tuning and Retrieval-Augmented Generation (RAG), helping you determine the most effective approach for your AI projects.
Navigating AI and Data Privacy Compliance: A Comprehensive Guide
Understand the critical intersection of Artificial Intelligence and data privacy regulations. This guide explores key compliance challenges, best practices, and strategies for organizations developing or deploying AI systems.
AI Change Management for Teams
Navigate the integration of Artificial Intelligence into your team's workflow with effective change management strategies. This lesson provides practical guidance for fostering adoption, addressing concerns, and maximizing the benefits of AI tools.
AI Research Summaries: Ensuring Accuracy and Credibility
Learn how to critically evaluate AI-generated research summaries, focusing on identifying and correcting unsupported superlative claims and statistics lacking sources.
Build Your Own FAQ Bot
Learn how to create and deploy your own Frequently Asked Questions bot to streamline customer support and provide instant answers.
AI Meeting Mastery: Optimizing Your Workflow
Learn how to leverage Artificial Intelligence to streamline your meeting preparation, note-taking, and action item tracking, freeing up your time for more impactful contributions.
Integrating AI with Zapier and Make (formerly Integromat)
Unlock the power of AI in your workflows by integrating intelligent automation with Zapier and Make. This lesson explores practical applications and best practices for connecting AI tools to streamline tasks and enhance productivity.
When Not to Automate: Realistic Expectations and Practical Scenarios
Explore the nuances of automation, moving beyond the hype to understand when it's truly beneficial and when it might be a costly mistake. This lesson focuses on realistic expectations and practical scenarios where automation might not be the best solution.
AI Investment ROI Calculator: A Realistic Approach
Learn how to realistically estimate the Return on Investment (ROI) for AI investments, avoiding exaggerated claims and incorporating data-driven insights.
Ensuring High-Quality AI Output at Scale
Learn strategies to maintain and improve the quality of AI-generated content when producing it in large volumes, focusing on accuracy, brand voice alignment, and substantiated claims.
Measuring AI Impact: Metrics and Evidence
Learn how to accurately measure the impact of AI initiatives by focusing on verifiable metrics and avoiding unsubstantiated claims. This lesson guides you in selecting and presenting data responsibly.
n8n and Microsoft Copilot Studio: Leading the Charge in Agentic Development
Explore how n8n and Microsoft Copilot Studio are at the forefront of the shift from traditional chatbots to advanced AI agents, shaping the future of work platforms.
The Evolution of Claude 3 Opus: From Groundbreaking to Foundational
Explore the historical significance and capabilities of Anthropic's Claude 3 Opus, tracing its impact and eventual integration into the lineage of advanced AI models.
AI Toolkit: Enhancing Statistical Analysis and Actionable Claims
Explore how an AI toolkit can revolutionize statistical analysis and empower you to make evidence-based, actionable claims.
A demo is not a robotics lab. Here is the tell.
How to watch a flashy AI-meets-robots video without thinking your warehouse job changed this morning.
AI Project Planning: Mastering Task Breakdown for Efficiency
Learn how to leverage AI tools to break down complex projects into manageable tasks, estimate timelines, and allocate resources effectively. This lesson focuses on practical application and strategic planning.
Understanding the AI Economic Divide: A Deeper Dive
Explore the complex economic landscape of Artificial Intelligence, focusing on the distribution of value and the challenges faced by different stakeholders. This lesson provides a nuanced perspective beyond hyped statistics, examining the real-world implications of AI adoption.
Debunking Cybersecurity Myths: A Critical Look at AI Claims
This lesson critically examines common claims about AI's impact on cybersecurity, focusing on the 'Mythos' AI model. We analyze the validity of assertions regarding vulnerability discovery timelines and AI's ability to deduce configuration patterns, urging a more evidence-based approach.
How to read a week of AI news for your actual job
Skim launches, ignore the stock plot, and keep one thing you will try at the desk.
Streamlining Operations with AI: Creating Standard Operating Procedures
Discover how Artificial Intelligence can revolutionize the creation of Standard Operating Procedures (SOPs), saving valuable time and improving operational efficiency.
Accelerating Content Creation with AI: A Pragmatic Approach
Explore the realistic speed benefits of AI in content creation, moving beyond hyperbole to practical applications and measurable improvements.
Unlocking Spreadsheet AI Insights for Claims Analysis
Discover how to leverage Artificial Intelligence within spreadsheets to analyze claims data, identify patterns, and generate actionable insights, moving beyond basic data manipulation to advanced analytical techniques.
AI Adoption Roadmap: Navigating the Future
Develop a strategic roadmap for successful AI adoption within your organization, focusing on practical steps and avoiding common pitfalls.
AI Policy Team Ground Rules
Establish clear and effective ground rules for your AI policy team to foster productive discussions, ensure ethical considerations are paramount, and drive successful AI policy development.
Leveraging AI for a Sustainable Competitive Advantage
Explore how Artificial Intelligence can enhance existing business capabilities to create a more robust and sustainable competitive edge, moving beyond hype to practical application.
AI Tool Selection Framework: A Practical Guide
Navigate the complex landscape of AI tools with a structured framework designed to help you make informed decisions based on your specific needs and objectives.
Navigating Common Pitfalls in AI Projects
Learn to identify and overcome common challenges in AI projects, from unrealistic expectations to implementation hurdles, ensuring successful and impactful AI adoption.
AI-Powered Data Cleaning Bootcamp
Learn to effectively clean and prepare your data for AI models using powerful AI-driven techniques. This bootcamp covers essential steps, tools, and best practices for transforming raw data into a usable format.
Optimizing Workflow with Custom GPTs
Learn how to create and leverage custom GPTs to streamline your tasks, manage prompts efficiently, and enhance productivity.
Chatbots vs. Agents: Clarifying the Distinction
Explore the fundamental differences between chatbots and AI agents, understanding their unique capabilities and applications in customer service and beyond.
Avoiding AI Hallucinations in Your Work
Learn how to mitigate AI hallucinations and ensure the accuracy and reliability of AI-generated content in your professional tasks.
Cut the adjectives before you paste the claim
A claims-hygiene drill for work writing, aimed at your next status doc.
Supercharge Your Inbox: AI-Powered Automation for Claims Professionals
Discover how AI can revolutionize your email workflow, saving valuable time and boosting efficiency in claims processing.
AI Product Pricing Strategy: Value-Based Approaches
Explore effective strategies for pricing AI-enhanced products and services, focusing on value-based methodologies and avoiding common pitfalls.
Midjourney V6: Limitations and Best Practices
Explore the current limitations of Midjourney V6 and learn best practices for generating high-quality AI art. This lesson addresses common issues and provides actionable advice for users.
Mastering On-Device AI: A Deep Dive into Google's Eloquent
Explore Google's Eloquent, an on-device AI for transcription and dictation. Learn its capabilities, limitations, and practical applications, with a focus on real-world projects and advanced AI skills.
Parse Error Handling and Retries in API Integrations
Master robust error handling and implement effective retry strategies for reliable API parsing and data integration.
Handling Parse Errors in JSON Parsing
Learn how to identify, handle, and recover from errors that occur during JSON parsing, ensuring robust data processing in your applications.
Turn a receipt photo into a row you still check
If expenses are part of your job: extract fields, then match the card statement. Not an accounting product.
Avoiding Common AI Project Failures
The recurring traps that sink AI initiatives and how to dodge them.
Building Custom GPTs for Your Workflow
Package your repeated prompts into a reusable custom assistant.
Cleaning Messy Data with AI
Deduplicate, normalize, and fix inconsistent records with AI assistance.
Critical AI Output Reading
Master the art of critically evaluating AI-generated content, developing an 'AI BS detector' to discern accuracy and reliability.
Chatbot, workflow, or agent — pick the smallest
One screen, three words. Stop renaming a saved prompt so a slide can say agentic.
Avoiding AI Hallucinations in Your Work
Techniques to cut made-up answers via grounding, citing, and asking for sources.
Connecting AI to Your Tools with Zapier and Make
Wiring AI into the apps you already use via popular automation platforms.
Building an AI Adoption Roadmap for Your Business
A phased plan from first experiments to embedded workflows.
Building Your Second Brain with AI-Powered Note-Taking
Discover how AI-powered note-taking tools can revolutionize your personal knowledge management and help you build a powerful 'second brain'. Learn practical strategies to capture, organize, and retrieve information effectively.
AI Policy: Setting Ground Rules for Your Team
A starter policy covering acceptable use, data handling, and disclosure for your team's AI tools.
Build vs. Buy AI Solutions: A Strategic Decision
Explore the strategic considerations for businesses deciding whether to build custom AI solutions or purchase off-the-shelf products. This lesson evaluates the pros and cons of each approach.
Building a Customer FAQ Bot
Stand up a grounded FAQ assistant from your existing help content.
Multimodal AI Explained: Understanding AI That Sees, Hears, and Speaks
Explore the exciting world of multimodal AI, where artificial intelligence can process and understand information from various sources like text, images, audio, and video, paving the way for more intuitive and powerful AI applications.
Creating Standard Operating Procedures with AI
Draft clear, repeatable SOPs from how you already do the work.
AI Ethics and Brand Reputation Management
Explore the critical intersection of Artificial Intelligence ethics and how they directly impact a brand's reputation. Learn to navigate ethical AI implementation to safeguard and enhance brand image.
AI-Assisted Decision Making in Claims Processing
Explore how Artificial Intelligence can enhance decision-making processes within the claims sector, focusing on efficiency, accuracy, and data-driven insights. This lesson revises existing content to provide a more grounded and evidence-based perspective on AI's impact, removing unsubstantiated claims about time savings.
AI for Project Planning and Task Breakdown
Turn a big goal into a structured plan with milestones and tasks using AI.
Open Source vs Closed AI Models
Trade-offs of running your own model versus calling a hosted API.
Understanding Token Context Limits and Their Impact on AI Responses
Explore the concept of token context limits in AI models, how they affect response generation, and strategies for working within these constraints. Learn to identify and mitigate issues arising from exceeding context windows.
The Operator Prompt System: Role, Constraints, Examples, Eval
A reusable four-part prompt you can run on any model: who it is, what it must not do, what good looks like, and how you will score the draft.
From Messy SOP to an AI-Assisted Workflow
Turn the procedure people actually run — not the wiki fiction — into a workflow with a clear AI job, human gates, and a five-case dry run.
Evaluate Model Output Without Trusting It
A ship/no-ship review for model drafts: citations, invented facts, and the only question that matters — would you send this to a customer with your name on it.
Build a First-Line Reply Library
Turn your last month of tickets into a small approved library so a model can draft first-line replies without inventing policy.
The 30-to-45-Minute Weekly AI Ops Cadence
A short weekly loop: review misses, promote or kill prompts, check the library, and run one small experiment — without standing up a fake AI program.
🧠Advanced
Judgment, privacy, and how to stay the person they keep — not how to open an agency.
Advanced Prompt Engineering: Structured Outputs, System Prompts & Multi-Step Reasoning
Move beyond simple prompts. Learn structured output formatting, system prompt design, and multi-step reasoning chains for complex business tasks.
Connect one inbox step. Do not boil the company.
One path: trigger, draft, human, send. For your job, not an enterprise maturity model with fake ROI math.
When someone says “agent” in a meeting
Enough vocabulary to stay in the conversation and say no to a raccoon with API keys. You are not here to deploy autonomous staff.
The workplace rules that keep you employed
What to do with the company AI policy, the kill switch, and the incident when a draft goes wrong. Not how to chair an enterprise transformation.
Show that AI helped your week. No invented percentages.
Personal, honest proof for a manager: what you drafted, what you checked, what still took you. Not an enterprise roadmap offsite.
Mastering Midjourney V6: Advanced Prompting Techniques
Dive deep into the advanced prompting strategies for Midjourney V6, focusing on precise control, stylistic consistency, and achieving complex visual narratives. This lesson refines existing knowledge by emphasizing evidence-based claims and data integrity within your prompts.
Measuring AI Impact: Metrics That Matter
Leading and lagging indicators that prove AI is working.
Pricing Your AI-Enhanced Products and Services
How to capture the value AI adds without underpricing or overreaching.
Evaluating AI Output Quality at Scale
Set up checks and scorecards so quality does not drift as you grow.
Calculating ROI on AI Investments
Frameworks to quantify time saved, revenue gained, and cost avoided from your AI initiatives.
Jobs where a fluent draft makes it worse
A stop list: high cost of being wrong, no source of truth, one-off judgment, and anything that should stay human.
Competitive Advantage Through AI
Discover where AI truly creates a durable business edge versus where it's just the cost of doing business.
Change Management for AI Adoption
Bringing a sceptical team along so the tools actually get used.
Privacy and Compliance When Feeding Data to AI
What you can and cannot safely send to third-party AI models, and how to stay compliant.
Fine-Tuning vs RAG: Which Do You Need
A practical decision guide between teaching a model and feeding it context.
Chain One Tool Without Vapor: An n8n First Agent
Build one boring n8n path — trigger, fetch, model, human approval, send — and write down what it will not do. No autonomous office.