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AI
Everyday AI
Updated Jan 2026

Guides that turn AI curiosity into real-world skill

Skip the wall of text. Find the right path, grab a template, and ship your next AI-powered workflow in hours—not weeks.

23

Templates, checklists & planners

2

Hands-on workshops

6

Industry playbooks

Start in 10 minutes

A short, structured path to your first meaningful AI win.

Pick a goal
Choose one task you want to improve this week (e.g., summaries, planning, or research).
Use a template
Grab a prompt pattern below and tailor it to your task.
Ship the result
Save your best prompt and use it again next time for speed.

Choose your learning path

Pick a starting point based on your goals. Each path links to the best modules and resources.

Browse all modules
Curious Beginner

You're new to AI and want to understand the basics before diving into practical use. Start here to build a solid foundation.

Best for

Students, professionals exploring AI, anyone with no prior AI experience

Module 1Module 2Module 3Module 6Module 7
Start Learning
Power User (No Code)

You want to master AI tools for maximum productivity without learning to code. Focus on advanced prompting and practical applications.

Best for

Professionals, content creators, knowledge workers seeking AI productivity gains

Module 1Module 3Module 4Module 6Module 7
Boost Productivity
Builder / Technical Track

You're interested in building with AI or understanding how it works under the hood. Explore technical concepts and integration.

Best for

Aspiring developers, technical professionals, anyone interested in AI development

Module 1Module 2Module 3Module 5Module 6Module 7
Start Building

Prompt Templates & Cheat Sheets

Search, skim, and expand only the templates you need. Build a personal library without the scroll fatigue.

Cheat Sheet Library

Search templates, checklists, and planners. Expand only what you need.

Showing 23 of 23 templates

Prompt Patterns

Reusable templates for common AI tasks. Copy, customize, and use these proven patterns.

7 templates
Role + Task + Context + Critique

Pro tip: Use when you need expert-level output with self-correction

You are a [role/expert] with expertise in [domain].

Your task: [specific task description]

Context: [audience, constraints, format requirements]

Examples (if needed): [show 1-2 examples]

After completing the task, critique your own response and identify one way to improve it.
Chain of Thought Reasoning

Pro tip: Helps AI show its work and catch logical errors

[Your question or problem]

Let's think through this step by step:
1. First, [step 1]
2. Then, [step 2]
3. Finally, [step 3]

Based on this reasoning, [conclusion]
Iterative Refinement

Pro tip: Build quality through multiple refinement cycles

[Initial request]

[After receiving response:]
"That's a good start. Now refine it by: [specific improvement 1], [specific improvement 2], and [specific improvement 3]."

[Continue iterating as needed]
Multi-Perspective Brainstorming

Pro tip: Generate diverse ideas by forcing different viewpoints

I need ideas for [problem/challenge].

Please provide ideas from three different perspectives:
1. As a [perspective 1, e.g., "creative designer"]
2. As a [perspective 2, e.g., "practical engineer"]
3. As a [perspective 3, e.g., "business strategist"]

For each perspective, give one concrete, actionable idea.
Summarization Template

Pro tip: Create focused summaries for any content type

Summarize the following [article/document/meeting notes] in [format]:

[Paste content]

Requirements:
- Length: [word count or bullet points]
- Focus on: [key themes or topics]
- Audience: [who will read this]
- Tone: [professional/casual/academic]
Writing Polish

Pro tip: Improve writing quality without losing your voice

I've written the following [type of content]. Help me improve it while maintaining my voice:

[Paste your draft]

Please:
1. Identify 3 areas that need improvement
2. Suggest specific revisions for each
3. Keep my casual/professional/[your] tone
4. Maintain the original message and intent
Learning Assistant

Pro tip: Master new concepts through structured explanation

I want to understand [concept/topic].

Please:
1. Explain it in simple terms (like I'm [age/background])
2. Provide a real-world analogy
3. Give me 3 practical examples
4. Suggest one hands-on exercise I can do to reinforce this

If I'm confused, I'll ask follow-up questions.

Responsible AI Checklist

Use this checklist before applying AI to important tasks or decisions.

8 templates
Data Privacy

Pro tip: Consider HIPAA, FERPA, NDAs, and company policies

Does this task involve confidential, personal, or proprietary information that shouldn't be shared with an AI tool?

Stakes Assessment

Pro tip: Higher stakes require more verification and human oversight

What are the consequences if the AI is wrong? Is this a high-stakes decision (hiring, medical, legal, financial)?

Bias Potential

Pro tip: AI can amplify historical biases in training data

Could this AI application disadvantage certain groups? Does it involve human judgment about people or opportunities?

Verification Plan

Pro tip: Never trust AI output without verification, especially for critical tasks

How will I verify the AI's output? Do I have the expertise to catch errors? Is there a human review process?

Transparency

Pro tip: Many contexts require disclosure of AI assistance

Should others know AI was involved? Am I required to disclose AI use (academic, professional, legal contexts)?

Organizational Policy

Pro tip: Check before using AI for work-related tasks

Does my organization have an AI use policy? Have I checked what's allowed and what requires approval?

Data Retention

Pro tip: Enterprise versions often have better data protection

What happens to the data I input? Will it be used for training? Can I delete it? Am I using the right version (e.g., Teams vs. consumer)?

Fallback Plan

Pro tip: Always have an alternative approach ready

If the AI fails or provides poor results, what's my backup plan? Am I overly dependent on this tool?

AI Project Planner

Template for planning your first AI mini-project.

8 templates
Project Goal

Pro tip: Example: 'Create a 5-minute podcast script about urban gardening'

What specific problem am I solving or outcome am I creating? Be concrete and measurable.

Success Criteria

Pro tip: Define clear, observable outcomes

How will I know this project succeeded? What does 'done' look like?

AI Tools Needed

Pro tip: Check tool availability and costs before starting

Which AI tools will I use? (ChatGPT, Claude, Midjourney, etc.) Are they free or paid?

Time Commitment

Pro tip: Start small and build consistency

How much time can I realistically dedicate? Break it into sessions (e.g., 3 sessions of 30 minutes).

Steps to Complete

Pro tip: Break the project into manageable chunks

List 3-5 concrete steps to finish this project. Make each step actionable.

Potential Challenges

Pro tip: Anticipate obstacles and plan workarounds

What could go wrong? How will I handle setbacks or unexpected results?

Learning Goals

Pro tip: Focus on skill development, not just deliverables

Besides the final output, what do I want to learn from this project?

Share & Reflect

Pro tip: Reflection deepens learning and builds momentum

Who will I share this with? How will I document what I learned?

Workshops & Projects

Build real workflows with step-by-step, hands-on projects.

Guided practice
Intermediate
Workshop: Build Your AI Research Assistant

Learn to create a custom AI workflow for academic and professional research. Use embeddings, vector databases, and retrieval-augmented generation (RAG) to build a system that can answer questions from your documents.

PracticeBuild
Start Workshop
Beginner
Workshop: Iterative Writing Workshop

Master the art of using AI as a writing partner. Learn prompt patterns for ideation, outlining, drafting, and revision. Build a personal writing workflow that maintains your voice while leveraging AI assistance.

Practice
Start Workshop

Industry Applications

Sector-specific playbooks with real workflows and ethical guardrails. Expand for details when you need them.

Healthcare

Enhancing diagnostic accuracy and early detection for better outcomes

  • Early disease detection through medical imaging analysis
  • Drug discovery through protein folding predictions
View details

Expanded Use Cases

  • Early disease detection through medical imaging analysis
  • Drug discovery through protein folding predictions
  • Patient monitoring with AI-powered wearable devices
  • Administrative automation (scheduling, billing, records)

Workflow snapshot

AI assists radiologists by flagging potential issues in scans. Doctors review AI findings, validate accuracy, and make final diagnoses. Systems learn from corrections to improve over time.

Ethical considerations

  • Ensure HIPAA compliance and patient privacy protection
  • Validate models across diverse populations to avoid bias
  • Maintain human oversight for all clinical decisions
  • Obtain informed consent for AI-assisted diagnosis

Education

Personalizing learning, automating routine tasks, and expanding access

  • Adaptive learning systems adjusting to individual student pace
  • Automated grading and personalized feedback for assignments
View details

Expanded Use Cases

  • Adaptive learning systems adjusting to individual student pace
  • Automated grading and personalized feedback for assignments
  • Accessibility tools (captions, text-to-speech, translations)
  • Virtual tutoring and 24/7 question answering

Workflow snapshot

Students interact with adaptive platforms that identify knowledge gaps. Teachers review AI insights to personalize instruction and provide targeted support. AI handles routine administrative tasks.

Ethical considerations

  • FERPA compliance for student data protection
  • Avoid surveillance culture and respect student privacy
  • Design for equity - ensure all students can access tools
  • Augment teachers, don't replace human connection and mentorship

Creative Industries

Enhancing ideation and production while respecting creativity

  • Generative art for rapid concept development
  • AI-assisted music composition and sound design
View details

Expanded Use Cases

  • Generative art for rapid concept development
  • AI-assisted music composition and sound design
  • Content generation for marketing campaigns at scale
  • Visual effects and post-production automation

Workflow snapshot

Creators use AI for ideation and rapid prototyping. AI generates variations that humans refine and polish. Final creative direction and artistic vision remain human-controlled.

Ethical considerations

  • Respect intellectual property and copyright laws
  • Credit human artists and contributors appropriately
  • Transparent disclosure of AI-generated content
  • Fair compensation models for training data creators

Business & Operations

Optimizing operations and customer engagement for efficiency

  • Targeted marketing with personalized customer campaigns
  • Lead scoring and sales process automation
View details

Expanded Use Cases

  • Targeted marketing with personalized customer campaigns
  • Lead scoring and sales process automation
  • 24/7 customer service through intelligent chatbots
  • Predictive analytics for demand forecasting

Workflow snapshot

Marketing teams use AI to generate campaigns at scale and personalize messaging. Sales automation scores leads and prioritizes outreach. Customer service combines chatbots with seamless human escalation.

Ethical considerations

  • Transparent data collection and usage policies
  • Respect customer privacy and obtain proper consent
  • Fair treatment in automated decision-making
  • Clear disclosure when customers interact with AI

Scientific Research

Accelerating discovery and analysis across disciplines

  • Protein structure prediction (AlphaFold) for biology
  • Climate modeling and environmental simulation
View details

Expanded Use Cases

  • Protein structure prediction (AlphaFold) for biology
  • Climate modeling and environmental simulation
  • Astronomical data analysis and pattern detection
  • Drug compound screening and material discovery

Workflow snapshot

Researchers use AI to analyze massive datasets and identify patterns. Models generate hypotheses that scientists test experimentally. AI handles computational heavy-lifting while humans provide domain expertise.

Ethical considerations

  • Maintain scientific rigor and reproducibility standards
  • Validate AI predictions through experimental verification
  • Transparent reporting of AI methods and limitations
  • Avoid over-reliance on black-box models without understanding

Legal Services

Streamlining research and document review for efficiency

  • E-discovery and contract analysis at scale
  • Legal research and case law precedent review
View details

Expanded Use Cases

  • E-discovery and contract analysis at scale
  • Legal research and case law precedent review
  • Document drafting and automated red-lining
  • Predictive case outcome analysis for strategy

Workflow snapshot

Lawyers use AI to search case law and identify relevant precedents. AI flags contract clauses requiring review. Attorneys validate findings, apply legal reasoning, and make strategic decisions.

Ethical considerations

  • Maintain attorney-client confidentiality and privilege
  • Ensure explainability for court compliance requirements
  • Human oversight required for all legal advice and strategy
  • Duty of competence requires understanding AI tool limitations

Want deeper industry insights?

Explore Module 9 for comprehensive sector-specific guidance, ROI analysis, and change management strategies.

View Module 9: AI in Your Industry

Looking for calculators?

Visit our Tools page to estimate token costs, calculate AI ROI, and measure time savings with interactive calculators.

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Ready to Put AI into Practice?

Explore our workshops or dive into Module 9 for sector-specific strategies and ROI analysis.