Compute and reuse
How reusing work and proven methods reduces repeated model work, and how to evaluate the result.
Start from work that already exists
When an agent generates a component from scratch, it has to work out the structure, produce the code, and correct mistakes. Retrieving a suitable saved component gives it an existing implementation to adapt and check.
The same principle applies to methods. A Playbook preserves the steps and checks for a recurring task. Retrieving that method removes the need to reconstruct it from an earlier conversation. Sirro places the saved work before the next execution of the task.
Use relevant context
A focused Pack groups the material needed for a job. The Pack supplies relevant conventions and examples in one retrieval, replacing repeated assembly of the same context. Keep Packs small enough to serve their purpose and update stale instructions.
In a company workspace, reuse extends across people and projects: a maintained implementation or method is available to the next authorized agent that needs it.
Account for the cost of reuse
Retrieval and reading consume resources too. Large assets, outdated instructions, or extensive adaptation can erase the benefit. Agents still need to validate retrieved work against the current task.
Sirro provides a reuse layer around the agents you choose. It does not change a model’s underlying inference cost. Reuse removes repeated generation from the workflow. The net change in total compute depends on the cost of retrieving, adapting, and checking the saved work.
Run a fair comparison
Choose a recurring task and define what a correct result looks like. Compare runs with and without the saved work. Include retrieval, context reading, generation, tool calls, retries, and human review in the comparison.
Record the model, task, saved version, token usage or reported provider cost, elapsed time, and outcome. Repeat across representative tasks before drawing a conclusion. Report changes in tokens, cost, and completion time alongside result quality; each measures a different part of the workflow.