The Iterative Optimization Loop

Last updated: 2025-07-03

Premature optimization can lead to unnecessary complexity and wasted effort. Instead, it's recommended to follow an iterative approach to context optimization:

1. Get it right: Start with a simple, correct solution that meets the functional requirements.
2. Test it right: Measure performance and cost using real data and scenarios.
3. Analyze: Evaluate whether the results meet your requirements.
4. Optimize: If not, make targeted improvements, prioritizing the changes that are likely to have the greatest impact.
5. Repeat: Re-measure and continue the loop as needed.

This process ensures that optimizations are both necessary and effective.

flowchart LR
    A[Build <br>a working solution] --> B[Measure: accuracy, latency, cost, resources usage]
    B --> C{Requirements <br> met?}
    C -- Yes --> D[Continue: new features or adjustments]
    D --> B
    C -- No --> E[Optimize]
    E --> B

Preventing optimization overload

Avoid attempting several optimizations at the same time. While it may seem efficient, making many changes at once can increase cognitive load, obscure the impact of individual improvements, and make troubleshooting more difficult.

Focusing on one or a few targeted optimizations at a time allows you to clearly measure their effects, reduces the risk of introducing new issues, and helps maintain a clear understanding of the system’s behavior. This disciplined, incremental approach not only streamlines the optimization process but also makes it easier to roll back changes if needed and ensures that each adjustment is truly beneficial.

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