Introduction
to AI
Who makes it, what chatbots can and cannot do, and why browser, terminal, cloud, and local tools feel so different.
Designed for a conversation of 1-6 people · approximately 60 minutes
Participant handout ↗ · Presenter guide ↗ · Explore 25 AI tools ↗
What have you already tried?
A chatbot?
ChatGPT, Claude, Gemini, Copilot, Meta AI, or something else?
A useful result?
Writing, research, planning, images, coding, or solving a practical problem?
A disappointment?
A wrong answer, generic prose, confusion, refusal, or a task it could not finish?
A concern?
Privacy, work, trust, cost, ownership, bias, or what happens next?
Do not call all of this “the AI.”
The company is not the chatbot. The chatbot is not one fixed model. The subscription is not the same thing as API access.
Several ecosystems, not one ladder.
OpenAI
ChatGPT, Codex, APIs, and GPT-family models.
Anthropic
Claude, Claude Code, APIs, and Claude-family models.
Gemini, Gemini Notebook/NotebookLM, Workspace tools, and APIs.
Microsoft
Copilot experiences across Windows, Microsoft 365, GitHub, and Azure.
Meta & open models
Model families that can be offered by many services or run more directly.
Many specialists
Search, images, video, voice, coding, research, and industry-specific systems.
Generative AI produces a plausible continuation from patterns and context.
It can transform information and create new combinations. It does not automatically know whether the result is true, current, authorized, or wise.
Generating an answer is not the same as finding a record.
Generation
Produces a response from learned patterns and the present context. Flexible, adaptive—and capable of confident invention.
Retrieval
Returns or consults an external source. More inspectable, but still dependent on source quality and interpretation.
Chatbots are unusually broad transformation tools.
- Explain unfamiliar material at a chosen level
- Draft, rewrite, summarize, compare, and translate
- Generate alternatives and expose overlooked questions
- Turn unstructured notes into a useful first structure
- Help write and understand software
- Work across text, images, audio, and other media
Fluency is not proof.
- A confident answer may still be false
- Knowledge may be missing, stale, or detached from sources
- The system may misunderstand your unstated context
- It does not inherit your legal or professional authority
- It may expose information you should not have supplied
- It cannot bear the human consequences of a decision
The same question, two chatbots.
Compare emphasis, assumptions, uncertainty, and what each system asks before answering.
The browser makes AI feel like a conversation.
Strengths
Accessible, visual, easy to start, good for questions, uploads, voice, images, research, and iterative discussion.
Boundaries
Usually sees only what you provide or explicitly connect. It may not share the state of your files, programs, or authenticated websites.
The terminal lets AI work inside an environment.
Strengths
Can inspect permitted files, run commands, test results, compare changes, and carry work across many related artifacts.
Boundaries
More capability creates more responsibility. Permissions, directories, version control, tests, backups, and review become essential.
It is not merely a different-looking chat box.
| Dimension | Browser chatbot | Terminal or coding agent |
|---|---|---|
| Starting point | Conversation | Files and a working environment |
| Typical context | Messages, uploads, connected services | Repository, commands, tests, tools |
| Typical output | Answer or artifact | Verified changes and runnable work |
| Primary risk | Believing an unsupported answer | Allowing an incorrect action |
| Human role | Questioner and evaluator | Director, reviewer, and authority |
Advice versus action on a real file.
The important step is not that AI can edit. It is that the change can be inspected, tested, accepted, or rejected.
Interface and location are separate choices.
| Question | Cloud service | Local system |
|---|---|---|
| Setup | Usually immediate | Hardware and software required |
| Capability | Often the strongest available models | Depends heavily on your machine and model |
| Privacy/control | Depends on provider, plan, and settings | Potentially greater, if the whole workflow stays local |
| Cost | Subscription, usage, or API charges | Hardware, electricity, setup, and maintenance |
| Availability | Internet and provider dependent | Can work offline and remain under your control |
The future is probably hybrid, not a winner-take-all contest.
Local context
Private files, browser sessions, devices, and organization-specific knowledge.
Cloud intelligence
Powerful models and services that would be difficult to operate independently.
Human authority
Purpose, judgment, consent, responsibility, and control of consequential actions.
Give the system something to work with.
Objective
What outcome do you actually need?
Context
What should it understand about you, the audience, and the situation?
Constraints
What must it preserve, avoid, verify, or leave for you?
Review
How will you decide whether the result is useful and trustworthy?
Not every AI action deserves the same permission.
reversible
reviewable
state-changing
consequential
Reading a selected page is different from publishing, purchasing, deleting, granting access, or sending a message.
From one conversation to a supervised publishing workflow.
Open the completed Why I Email Myself campaign in PubDesk. Show status and proof. Do not publish live.
From chatbot to collaborator
What changes when AI can work with files, browsers, and workflows—but the human still controls the consequential actions?
Five things to keep.
- Vendor, product, model, interface, and location are different
- Generation is not the same as retrieval or proof
- Context improves results; review creates reliability
- Browser, terminal, cloud, and local are choices—not rankings
- Capability does not grant authority
What became clearer—and what still feels confusing?
Clearer?
What distinction helped?
Unresolved?
What still feels confusing or unbelievable?
Next?
Which demonstration should we explore?
Explore the products directly.
- OpenAI: ChatGPT
- OpenAI: Codex
- Anthropic: Claude
- Anthropic: Claude Code
- Google: Gemini
- Google: Gemini Notebook / NotebookLM
- Microsoft Copilot
- GitHub Copilot
- Meta AI
- Ollama
- LM Studio
- Kurka Labs
Product names, capabilities, prices, and availability change. Verify current details before making a purchasing or deployment decision.