I don't agree. In "none" thinking mode, Terra serves a useful purpose where medium-grade intelligence is needed. Luna doesn't cut it.

Hardly enough time had passed to develop the data to come to a conclusion. Users can take time to build interest.

The users of Terra disagree. Specifically, Terra is useful when medium-grade intelligence is needed in instant ("none" thinking) mode.

Hardly enough time had passed to develop the data to come to a conclusion. Users can take time to develop an interest.

I have found it worked quite well as the workhorse model in my hermes agent.

I disagree. After a bit of experimenting, I actually found Terra to be a very good workhorse model on none-to-medium reasoning, and I actually quite prefer its code to Sol's in many cases. It has less of a complexity to over-complicate things. Where Sol would have a sea of try/except and recoveries for situations that are structurally impossible, Terra would just write nice, sequential code.

Maybe for one-shotting large things Sol is better, but for prod code where I decompose into smaller tasks and read all the code I favored Terra.

Sol 5.6 was still king for architecture/research in my workflow, though.

Your employer should reconsider. Sol high is cheaper than Terra max and smarter, when measured per task. ie even if tokens are more expensive Sol can often do a job with fewer tokens.