LLM (Large Language Model)
A Large Language Model (LLM) is an artificial intelligence system trained on massive text datasets to understand and generate human-like text.
Key Characteristics
- Scale: Billions of parameters trained on internet-scale text data
- Generalization: Can perform many tasks without task-specific training
- Context Window: Amount of text the model can process at once (Claude: 200k tokens)
- Inference: Using the trained model to generate responses
Examples of LLMs
| Model | Developer | Use Case |
|---|---|---|
| Claude | Anthropic | SpecWeave's recommended model |
| GPT-4 | OpenAI | Alternative for some workflows |
| Gemini | Multi-modal capabilities |
Why This Matters for SpecWeave
SpecWeave leverages LLMs to:
- Generate specs from natural language descriptions
- Plan implementations with architectural decisions
- Execute tasks autonomously with code generation
- Validate quality through intelligent review
Related Terms
- Inference - Using trained models
- Intelligent Model Selection - Choosing the right model