Transformer
The neural network architecture that powers virtually all modern large language models and AI agents. Introduced in 2017 ('Attention Is All You Need'), transformers process input text in parallel using self-attention mechanisms that capture relationships between all words simultaneously—unlike earlier architectures that processed text sequentially. GPT, Claude, Llama, and Gemini are all transformer-based. Understanding transformers helps explain why modern agents can reason about long contexts and generate coherent, contextually aware responses.
Frequently asked questions
- Do I need to understand transformers to deploy AI agents?
- No. Transformers are the engine under the hood—you don't need to understand internal combustion to drive a car. But knowing the basics (attention, context windows, token processing) helps you make better decisions about model selection, prompt design, and cost optimization.