Just a quick note on @openclaw after having built 11 agents in 2 multi-agent instances: Julia heads an accounting team of 5, together with Kate (reader), Fulvia (editor), Sophia (analyst), and Flavia (tester); Juno heads an executive staff of 6, together with Venus (comms), Minerva (analyst), Flora (editor), Diana (organizer), Vesta (Q&A). (the 2 teams have just started cooperating via their leaders). These agents are really amazing, but it can cost a lot of $ to get them working properly. Development, operations, and maintenance will dry your premium token budget very fast if you rely on SOTA models (and you don't want to default to budget models, because it takes one wrong call to f.up hard). Here is the key takeaway: smart LLM routing will become increasingly necessary to route the optimal model for each call, with the potential of saving up to 90% (that's because 90% of calls don't require SOTA). Tools like @clawrouter do a decent job, but they use hardcoded rules to route LLM calls. We need smarter light weight AI routers to do the job. This is what platforms like @BotScanner_AI and #AutoBench can help with. And we're working on it. Stay tuned...
