Nah; I can use my token budget across both providers this way, use tokens more sparingly with smaller models for heavy text in/out (why pay Opus prices to babysit a PR? run tests?), and you'd be surprised when the agents talk to each other and "role play" how much this improves things like the UX as well as technical design which are more subjective.

Distinguished Member of Technical Staff, for example, is asked to "expand the solution space" which I find has a strong effect on approaches considered (it doesn't know what was already considered on the main thread; only the domain and problem space).

This also helps with context growth since the sub-agents do the heavy lifting (e.g. search, read docs) and just provide the key bits back to the lead.

Like you, I was a single-model, single-TUI user up until three weeks ago when I picked up Paseo and it is the only tool that I've found that has significantly positively improved my throughput without sacrificing quality of product.

Is it "larping"? I ran an eval today on a contract ingest and extract agent I'm working on. Changing the <role> fragment of the prompt lifted the results by +7 points by simply changing the text to the effect of "You are a senior partner at a prestigious law firm that focuses on reading licensing contracts..." and some bits about the content the agent is reviewing + objective. No one would believe it without an eval.

Claude docs explicitly say to LARP[0]:

    > Give Claude a role
    > 
    > Setting a role in the system prompt focuses Claude's behavior and tone for your use case. Even a single sentence makes a difference

My conclusion: the agents like to LARP so I'm happy to LARP with them.

[0] https://platform.claude.com/docs/en/build-with-claude/prompt...

SlopCodeBench 10/2026 – Opus 5.5, Astra wins overall, xhigh considered harmful