I've taken to using them as micro-review subagents at development milestones, where a "frontier - 1" model like Opus or Sol launches 10-15 of them on small review tasks that each run for ~10 minutes. Costs about $1 per cycle, and they usually catch something Astra or Fable didn't. Then the orchestrator validates each claim before passing it back to the planning session so we can fold the findings in.
Perhaps because they are dumber, they produce better results? IMO an excellent well-tuned harness combined with a "frontier minus x" model produces the highest quality result. DS4.1 and Qwen3.8, far from being a compromise, legit give me better results. For my personal definition of "better".
And once frontier models can architect (turn business requirements into engineered systems) then I guess no one needs a job because that’s the digital singularity.
Perhaps they simply don’t advertise it and investors (currently) love companies that spend heavily on frontier models. That said, OW models, especially when combined with RAG, work quite well, and given the current state of the industry, they may be the only sensible way to keep inference costs under control.
Why do you think OAI etc are all up in arms? They hate what’s going on. Most here are delusional.
I work in a very large market cap firm and i’m telling you - more and more managers are pushed to get their teams to use open source and squeeze employees to get the max out of them.