Agent Systems: Resource-Aware Optimization

Problem

Agent systems consume model calls, context, retrieval, tools, worker slots, and time. Maximizing answer quality without measuring cost and latency is not a production design.

Intent and structure

task difficulty and value → resource policy → method selection → measured result

The main trade-off is among quality, latency, and cost, with reliability and reproducibility as additional constraints.

Practical policies

• Use deterministic code for exact computation.
• Use small models for classification, extraction, or formatting.
• Reserve stronger reasoning or deep search for high-value uncertainty.
• Reduce repeated work with caching, context pruning, batching, and early stop.
• Use asynchronous execution for long-running work and checkpoints for resume.

Degradation testing

Measure what happens when model quality, retrieval quality, or tool availability decreases. A graceful fallback should expose lower confidence or reduced scope, not silently claim the original quality.

Figure

Figure: a policy routes work among cheap, targeted, deferred, and stopped execution paths.