Context Window Allocation: Budgeting Tokens for Maximum Signal

Every token has a cost and an opportunity cost.

Over-allocating to system prompts can crowd out relevant context.

Split budgets between system instructions, memory, and retrieved evidence.

Tune based on task complexity and user behavior.

Adjust budgets per request based on predicted complexity.

Use smaller prompts for low-risk tasks to save tokens.

Summaries can reclaim budget while preserving signal.

Validate summary accuracy to avoid compounding errors.

Measure task success against token usage.

Optimize for cost per correct answer, not just accuracy.

Allocate a fixed floor for system prompts to preserve policy intent.

Cap user history to the last meaningful turns, not the full chat.

Reserve budget for retrieval so evidence is not crowded out.

Use dynamic caps based on model size and max context.

Shrink prompts automatically when latency targets are exceeded.

Prefer structured memory over raw transcripts to save tokens.

Track wasted tokens per request to guide pruning rules.

Benchmark token allocations against user satisfaction scores.

Block low-signal content from entering the context window.

Add relevance scoring before injecting retrieved chunks.

Maintain a minimum evidence threshold for high-stakes answers.

Summarize long documents into structured facts when possible.

Validate summaries against source snippets to prevent drift.

Log context composition so debugging is straightforward.

Use token alerts to detect runaway context growth.

Apply policy checks to user-provided context before inclusion.

Prefer canonical sources when multiple documents conflict.

Drop repeated chunks to avoid wasting budget on duplicates.

Cap tool outputs to prevent runaway token usage.

Track context quality scores to guide pruning heuristics.

Store context snapshots for critical decisions to support audits.

Define max chunk counts per source to prevent source dominance.

Add fallback modes when retrieval quality drops below thresholds.

Is bigger context always better? Not if it includes irrelevant content.

What is the fastest improvement? Trim system prompts and low-value history.

How do I detect waste? Track token usage vs. task success rates.