Getting Started with AI

Welcome to Site A. This series covers the AI landscape in 2026 and what it means for developers building modern applications.

What Is AI in 2026?

Artificial intelligence today is dominated by large language models (LLMs), generative image and audio systems, and increasingly capable AI agents. These systems learn statistical patterns from vast datasets and can generate human-quality text, code, images, and more on demand.

Three categories define the current landscape:

• Generative models — produce content: text, images, audio, video
• Reasoning models — solve multi-step problems, write and execute code
• Agents — take actions autonomously using tools and APIs

Key Milestones That Got Us Here

| Year | Milestone | |------|-----------| | 2017 | Transformer architecture introduced ("Attention Is All You Need") | | 2020 | GPT-3 demonstrated large-scale language generation | | 2022 | ChatGPT brought LLMs to mainstream users | | 2023 | Open-source models (Llama) democratized local AI | | 2024 | Multimodal models — text, image, and audio in one model | | 2025–2026 | Agents and reasoning models handle complex real-world tasks |

Why Developers Should Care

AI is no longer just a research topic — it is a practical building block. Developers today use AI to:

1. Generate and summarize content at scale
2. Write and review code with AI pair programmers
3. Automate workflows with agents that call APIs and make decisions
4. Build intelligent interfaces that respond naturally to user input

What's Next in This Series

To understand how these models work internally, read Understanding Large Language Models. When you are ready to build, Building AI-Powered Applications walks through choosing an API and writing your first AI-powered pipeline.