Designing around token limits, memory, and conversation persistence.
--- name: context-window-design-28ae430e395e description: Designing around token limits, memory, and conversation persistence. --- # Context Window Design Every AI model has a finite context window. Designing within this constraint — and designing the user experience around it — is a core skill for AI product design. ## The Context Window as a Design Material The context window is not just a technical limitation. It's a design material: - **What goes in**: System prompts, conversation history, retrieved documents, tool results, user preferences - **What gets dropped**: Older messages, less relevant context, verbose instructions - **What the user sees**: The conversation as presented may differ from what the model actually processes Designers must understand context window allocation to design reliable experiences. ## Memory and Persistence Users expect AI to remember. Design for different memory horizons: - **Within-conversation memory**: What was said earlier in this chat. Usually handled by the context window itself. - **Cross-conversation memory**: Preferences, past decisions, ongoing projects. Requires explicit memory systems. - **Shared memory**: Context shared across multiple users or agents. Requires careful privacy design. ## Strategies for Limited Context - **Summarisation**: Compress earlier conversation into summaries to free up tokens - **Retrieval-augmented generation**: Pull in relevant context on demand rather than keeping everything loaded - **Priority ordering**: Put the most important context closest to the prompt (recency bias in attention) - **User-controlled context**: Let users pin, remove, or prioritise what the AI remembers - **Graceful degradation**: When context is lost, acknowledge it rather than hallucinating continuity ## Design Artefacts - Context budget allocations (how many tokens for system prompt, history, retrieval, etc.) - Memory architecture diagrams showing what persists and what's ephemeral - Context overflow UX flows (what happens when the window fills up) - User-facing memory controls specification--- name: context-window-design-28ae430e395e description: Designing around token limits, memory, and conversation persistence. --- # Context Window Design Every AI model has a finite context window. Designing within this constraint — and designing the user experience around it — is a core skill for AI product design. ## The Context Window as a Design Material The context window is not just a technical limitation. It's a design material: - **What goes in**: System prompts, conversation history, retrieved documents, tool results, user preferences - **What gets dropped**: Older messages, less relevant context, verbose instructions - **What the user sees**: The conversation as presented may differ from what the model actually processes Designers must understand context window allocation to design reliable experiences. ## Memory and Persistence Users expect AI to remember. Design for different memory horizons: - **Within-conversation memory**: What was said earlier in this chat. Usually handled by the context window itself. - **Cross-conversation memory**: Preferences, past decisions, ongoing projects. Requires explicit memory systems. - **Shared memory**: Context shared across multiple users or agents. Requires careful privacy design. ## Strategies for Limited Context - **Summarisation**: Compress earlier conversation into summaries to free up tokens - **Retrieval-augmented generation**: Pull in relevant context on demand rather than keeping everything loaded - **Priority ordering**: Put the most important context closest to the prompt (recency bias in attention) - **User-controlled context**: Let users pin, remove, or prioritise what the AI remembers - **Graceful degradation**: When context is lost, acknowledge it rather than hallucinating continuity ## Design Artefacts - Context budget allocations (how many tokens for system prompt, history, retrieval, etc.) - Memory architecture diagrams showing what persists and what's ephemeral - Context overflow UX flows (what happens when the window fills up) - User-facing memory controls specification
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