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Demystifying AI

A Visual Journey Through Artificial Intelligence

Discover how artificial intelligence actually works, from vectors to real-world applications.

Why This Matters Now

AI tools release major updates weekly, not yearly. What you learn today might change next month.

The skill isn't knowing specific tools — it's learning how to learn.

This guide focuses on understanding the fundamentals, so you can adapt as tools evolve.

"Forget annual targets. Build the capacity to learn, adapt, and create value."— Ro Fernandez

How AI Thinks: Finding Neighbors

To understand AI tools, you need to understand one core concept:

AI converts everything into points in space, then finds what's nearby.

Everything you type becomes a point. AI finds what's closest to that point.

Step 1: Words Become Numbers

AI can't read words directly. It converts them into numbers called "embeddings."

"sad" = 0.2     "happy" = 0.8

Words with similar meanings get similar numbers. The distance between numbers represents how related concepts are.

Distance = Similarity

Step 2: Adding Dimensions

One number isn't enough. AI uses multiple dimensions to capture meaning.

Now words have position AND emotion. The second dimension might represent sentiment intensity or energy level.

"joyful" is near "happy" but higher energy

Similar words cluster together in this 2D space.

The Full Picture: Thousands of Dimensions

Real AI systems use hundreds or thousands of dimensions, not just 2 or 3.

Similar ideas cluster together in this high-dimensional space.

This is why AI can understand context, nuance, and relationships between concepts. The magic isn't magic — it's math finding patterns.

Different Tools for Different Jobs

Each AI tool has strengths. Here's when to use what:

ChatGPTBest for: general questions, writing, brainstorming. Most widely used and versatile.
GeminiBest for: image analysis, Google Workspace integration, multimodal tasks.
ClaudeBest for: long documents, enterprise use, complex reasoning tasks.
GrokBest for: real-time information, research, current events.

Three Ways to Use AI

You can interact with AI at different levels, depending on your needs:

GUIPoint and click interfaces. Best for: beginners, quick tasks, visual learners.
CLICommand-line interfaces. Best for: power users, automation, batch processing.
CodeAPI and programming. Best for: developers, custom integrations, maximum control.

Most people start with GUI, but CLI unlocks 10x more capability.

Every Department Is Using AI

AI isn't just for tech teams. Here's how different departments are applying it:

Engineering
Code review, debugging, documentation
Marketing
Content creation, A/B testing, analytics
Operations
Process optimization, SOPs, training
Research
Literature review, data analysis, synthesis

How AI Changes Technical Work

For technical professionals, AI acts as a force multiplier:

  • Code review and debugging in seconds instead of hours
  • Documentation that actually gets written and stays updated
  • Learning new technologies 10x faster with AI as your tutor

Not replacing — multiplying output.

The human still makes the decisions; AI handles the repetitive heavy lifting.

The Hidden Revolution: Documentation

Standard Operating Procedures (SOPs) — the step-by-step guides every organization needs but rarely writes.

Days Hours

AI turns rough notes into polished documentation, making institutional knowledge shareable. What used to take days of writing and formatting now happens in hours.

This alone is transforming how organizations preserve and transfer knowledge.

What's Actually Happening to Jobs

Jobs aren't disappearing — they're transforming. The question isn't whether AI will change your role, but how.

"AI won't replace you, but someone using AI might."

Those who learn to work with AI will have a significant advantage. Those who don't risk being left behind.

"When teams are strong, AI becomes a force multiplier. When teams lack clarity or development, AI reveals that quickly."— Rebecca Avery

The New Required Skills

Success with AI requires three core competencies:

  • Prompt engineering — knowing how to ask the right questions to get useful results
  • Critical evaluation — knowing when AI is wrong, biased, or hallucinating
  • Tool fluency — adapting quickly as new tools emerge and existing ones evolve

These skills compound: the better you get at one, the easier the others become.

Teaching in an AI World

Students will use AI — the question is whether we ban it or harness it.

Process over product.

The goal: students who can think, not students who can type prompts. Practical strategies:

  • Require students to show their work and explain their reasoning
  • Use AI for brainstorming and drafts, but require human refinement
  • Teach AI literacy alongside subject matter
  • Focus assessments on understanding, not just output

Think of AI as Your Smartest Intern

Think about a task that takes you a long time. Maybe it's:

  • Organizing research notes or content
  • Researching a topic and synthesizing findings
  • Planning a project or event
  • Reviewing and summarizing documents

If you can explain it to someone else step-by-step, you can guide AI to do it.

Break down your process into clear steps. Write them out in order. Then ask AI to follow those same steps. This approach — called "chain-of-thought" prompting — helps AI understand and replicate complex tasks.

Start with something you already do well. That way, you can evaluate whether AI is following your process correctly and refine your instructions.

"Learning without doing is wasted. How horrible to waste those hundreds of hours I spent learning, and not turn it into action."— Derek Sivers

Questions?

Let's discuss.

This guide covers the fundamentals, but every organization's AI journey is unique.

For more resources or to continue the conversation, reach out.