Overview › 6Topologies › b.Parallelizing

Parallelizing

Decompose work across parallel agents. 3 optimizations.

1. i.

   Parallel tool execution for read-only calls

   Let the model put several independent read-only tool calls (searches, fetches, file reads) in one turn and have the harness run them at once, while calls that write, share state or need another call's result run one at a time in the order the model emitted them.

   Lower costFasterMixed quality

   Tier 3 · tuning · changes control flow · any agent · 6 sources, 3 measured

2. ii.

   LLM map-reduce

   Give each piece of a large or untrusted input its own tool-less model call that sees only that piece and must answer in a fixed schema, then combine the answers in code or in a reducer that never sees the raw text.

   More secureBetter governanceMixed qualityMixed costMixed performance

   Tier 2 · reliability · changes control flow · any agent · 6 sources, 4 measured

3. iii.

   Use multi-agent orchestration only for breadth-first, independent sub-tasks

   Spawn parallel sub-agents when the work splits into independent, breadth-first parts with little shared context; expect about 15x the tokens of a chat and up to 90% less wall-clock.

   FasterMixed qualityHigher cost

   Tier 4 · restructuring · changes control flow, context · any agent · 22 sources, 7 measured