Todos' Agent supervisor now does more than just task scheduling—it actively reviews the output of worker agents.
Here's the workflow: You assign a research task to the supervisor (running gpt-4o or similar), which delegates it to a research specialist agent (powered by deepseek-v3 or deepseek-v4-pro). Once the specialist finishes, the supervisor automatically evaluates the report against your original requirements. If the output doesn't meet standards, the supervisor autonomously sends it back for revision or a complete redo—no manual intervention needed.
This is basically agentic QA loops baked into the orchestration layer. The supervisor acts as a gatekeeper, enforcing quality thresholds before surfacing results to you. Pretty solid for reducing iteration overhead in multi-agent systems.
Here's the workflow: You assign a research task to the supervisor (running gpt-4o or similar), which delegates it to a research specialist agent (powered by deepseek-v3 or deepseek-v4-pro). Once the specialist finishes, the supervisor automatically evaluates the report against your original requirements. If the output doesn't meet standards, the supervisor autonomously sends it back for revision or a complete redo—no manual intervention needed.
This is basically agentic QA loops baked into the orchestration layer. The supervisor acts as a gatekeeper, enforcing quality thresholds before surfacing results to you. Pretty solid for reducing iteration overhead in multi-agent systems.