Context Window Strategies: Making the Most of Long-Context LLMs

Million-token context windows tempt teams to dump entire repos into prompts. That is expensive, slow, and often less accurate than targeted retrieval.

When Full Context Helps

Single-file refactors, analyzing one large document, comparing a few long contracts.

When Retrieval Wins

Whole codebases, ticket backlogs, and wiki sites-embed, filter, rerank, then pass top-k chunks.

Compression Techniques

Summarize conversation history. Use hierarchical memory (session summary + recent turns). Strip comments and generated noise from code context.

Cost Control

Track tokens per request. Cache system prompts and embeddings. Batch non-urgent analysis offline.

Conclusion

Long context is a tool, not a strategy. Combine sliding windows, RAG, and summarization-measure accuracy per dollar.