Context Windows: Your Agent's Memory Limit
Every LLM has a context window - the maximum amount of text it can process at once. This is your agent's working memory.
Context Window Sizes (2024)
| Model | Context Window | ~Tokens |
|---|
| GPT-4 Turbo | 128K | ~96,000 words |
| Claude 3 | 200K | ~150,000 words |
| Gemini Pro | 1M | ~750,000 words |
Sounds like a lot, right? Wrong.
Why Context Management Matters
In production, context fills up fast:
And that's a simple case! Real agents often hit context limits.
Symptoms of Poor Context Management
- Truncation: Important information gets cut off
- Forgetting: Agent loses track of earlier conversation
- Confusion: Too much irrelevant info crowds out relevant
- Cost: Larger context = more tokens = more $$$
Context Management Strategies
- Summarization: Compress old messages into summaries
- Sliding Window: Keep only recent N messages
- Relevance Filtering: Only include relevant past context
- Chunking: Split large documents, retrieve relevant chunks
- Tiered Memory: Hot (context) / Warm (cache) / Cold (database)