Last updated: 2025-10-20

ChatGPT & OpenAI — A Practical, Linked Tutorial for Beginners

New to ChatGPT? Start here. This page explains what it is, where it came from, how it works at a high level, and concrete ways you can use it today—with trustworthy links to official sources for every major claim.

What is ChatGPT?

ChatGPT is a conversational AI by OpenAI. It understands prompts and responds in natural language, and the most recent flagship models can reason across text, images, and audio in real time. The original public research preview launched on November 30, 2022, using techniques like instruction following and RLHF to make answers more helpful and safer.

Why people care

Individuals and teams use ChatGPT for drafting, editing, tutoring, coding, data cleanup, customer support, and more. For product-level improvements, see the evolving ChatGPT Release Notes and OpenAI News.

Quick timeline

  • Nov 2022 — Public research preview of ChatGPT (intro).
  • Mar 2023 — GPT-4 technical report; strong benchmark performance and early multimodal work.
  • Nov 2023 — DevDay updates with longer context & cost reductions (summary).
  • May 2024 — GPT-4o (“omni”) enables real-time, multimodal reasoning for chat.
  • Late 2024 — o1 reasoning models emphasize deeper multi-step thinking.
  • 2025 — Continued updates (watch release notes).

What ChatGPT can do (today)

  • Write & edit: emails, blogs, docs; adjust tone/reading level. See product updates.
  • Learn & tutor: step-by-step explanations with quizzes; see GPT-4 report for context.
  • Code & debug: generate functions, explain errors; follow DevDay announcements.
  • Analyze data & docs: summarize, extract, outline; check release notes for file features.
  • Reason across modalities: talk through images or voice with GPT-4o.
  • Create images: see 4o image generation.
  • Integrate via API: start with the ChatGPT & Whisper APIs.

How it works (30 seconds)

ChatGPT runs on large language models (LLMs) trained on vast corpora. At inference time, the model predicts plausible next tokens, guided by safety policies and tuned with RLHF. For strengths/limits see the GPT-4 technical report and the o1 reasoning overview.

Safety, privacy, and limits

Models can make mistakes (“hallucinations”), be sensitive to phrasing, or miss brand-new events. Good practice: ask for sources, iterate, and fact-check. For policy-level views, see OpenAI’s public help center and safety posts.

Getting started (absolute beginner)

  1. Pick an entry point: Use ChatGPT in your browser/app, or the OpenAI Platform for programmatic use.
  2. Choose a model: For mixed media, try GPT-4o; for complex multi-step tasks, explore o1 (plan/availability may vary).
  3. Start simple prompts: “Explain <topic> in 3 bullets,” “Summarize this article with key quotes,” “Diagnose this error stack.”
  4. Iterate: Ask to shorten, add sources, compare options, or convert to a checklist.
  5. Add files, images, or voice: Upload a file or image and discuss it; try live voice with GPT-4o.

Keep an eye on release notes and OpenAI News so this page stays fresh with minimal edits.

What’s different about “o1” reasoning models?

Classic LLMs are great at fluent text but can drift on complex logic. The o1 series allocates more compute to “think before answering,” improving multi-step tasks in code, math, and analysis. See system cards and examples on the o1 hub.

Real-world examples

  • Customer support: Assistants triage and draft replies; see case studies highlighted in OpenAI News.
  • Developers: Lower latency/cost and longer context from DevDay-era updates—see post.
  • Analysts/ops: Rapid summarization, extraction, and outline generation; track features.

Want to build? Start with the API quickstart and model chooser on the OpenAI Platform.

Copy-paste prompts to try

Everyday writing Tone & polish

Prompt: “Rewrite the text below in a warm, concise tone. Keep the technical details, remove filler, and end with a 3-step action list. Then suggest a 60-character title.”

Learning Practice

Prompt: “Teach me the basics of ____ in 5 short sections: overview, key terms, example, misconception, 3 quiz questions with answers.”

Coding Debugging

Prompt: “Here’s an error & stack trace. Diagnose the likely cause, show a minimal reproducible example, and propose 2 fixes—one quick, one robust. Ask me 3 clarifying questions.”

Analysis Docs & data

Prompt: “Extract a clean table of entities, attributes, and values from the text below. Then produce a 5-bullet executive summary with 2 limitations called out explicitly.”

Developer corner (API quickstart)

Code blocks below intentionally render single-column for easy copying, even on this two-column page.

1) Create an API key

Visit the OpenAI Platform to create a key. Store it securely (for local testing use environment variables).

# macOS/Linux
export OPENAI_API_KEY="sk-...yourkey..."

# Windows (PowerShell)
setx OPENAI_API_KEY "sk-...yourkey..."

2) Send your first request

Use the official SDKs or HTTPS. See the model chooser and pricing in the Platform UI.

import os, requests, json

API_KEY = os.getenv("OPENAI_API_KEY")
url = "https://api.openai.com/v1/chat/completions"

payload = {
  "model": "gpt-4o-mini",
  "messages": [
    {"role":"system","content":"You are a helpful assistant."},
    {"role":"user","content":"Explain RLHF in 3 bullets with a friendly tone."}
  ]
}

resp = requests.post(url,
  headers={"Authorization": f"Bearer {API_KEY}",
           "Content-Type":"application/json"},
  data=json.dumps(payload))
print(resp.json())

Explore endpoints, tools, and evals from the OpenAI docs.

Attribution & editing tips

  • Use inline links for every substantive claim; favor official OpenAI URLs.
  • Include a small “Last updated” note (top right) and revisit quarterly.
  • When you mention fresh features, point to the release notes.

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