One model does not need every job
LegalOn first gave developers broad access to its strongest coding model, then found that unlimited high-end usage would exceed its budget. Its AI Development Center began testing model choices and sharing guidelines so developers could match the model to task complexity.
The company says routine code implementation and automations can use GPT‑6 Luna; standard design, analysis and documents can use GPT‑6.1 Sol; and complex architecture or orchestration can use GPT‑6 Astra. Administrators set monthly department and individual limits, with room for newer business areas to experiment.
Reported savings with speed maintained
LegalOn reports an estimated 65% reduction in daily costs and around 20% efficiency gains in mature business areas. It says development speed stayed steady because teams could run some tasks in parallel and move to a stronger model when a task needed it.
This is a company-reported operating result rather than a controlled cross-company comparison. Still, it points to a concrete agent-era management shift: model routing and budgets become part of software delivery. The cost question is not simply which model is cheapest, but how to give each task enough capability without paying frontier rates for routine work.
Source published 2026-10-08. Coverage is based on the maker’s announcement and demonstration.