AI product costs often become unpredictable not because the model is too expensive, but because the architecture calls the model too many times for the same operation.
Cogweald intentionally keeps chapter generation to one LLM call per world. That call produces the content, summary, time span, character updates, thread updates, and long-term facts together.
This is not about cramming everything into one prompt. It starts with designing an output contract so one reasoning result can become one complete domain event.
The benefits are straightforward:
- Costs are easier to estimate.
- Each chapter has one source of truth for its decisions.
- A summary model cannot contradict a content model.
- Retry semantics are easier to reason about.
- Token usage is easier to observe.
Single-call is not always the right answer. Workflows that need multiple validation stages or tool interactions may need multiple calls. Before splitting, ask whether those calls truly need different reasoning boundaries.
