Totally agree, my last answer was also in 2021; I remember trying to jump back in and just feeling like the quality of questions was so poor and all of the many "homework" questions felt dirty to answer because I'm clearly helping someone cheat.
I actually got hounded / insulted on a couple of my last answers for not providing timely responses to their comments on my answer and that was the last straw.
I don’t feel like reality is so interesting that CC devs are sitting in a room theorizing how to extract the most profit from their users.
I’m much more inclined to believe they just don’t _care_ about cost, and profit is an ancillary benefit to their functionality above all else.
Just recently they released auto idle-compaction for large sessions about to miss the cache window. If they were so profit driven I can’t imagine they’d have built this to begin with, that’s free tokens from your perspective.
A smart company would A/B test changes and choose based on lifetime value vs. average session value. The compaction is going to happen anyway, does idle compaction increase the length of a session or the amount of sessions per user?
You’re making a straw man argument out of the nature of what jobs are for, of course they are to help a company make a profit.
I don’t think the CC’s teams have hidden motives to optimize for token inefficiency as the OP I replied to implies.
A reality where a secret cabal of CC engineers are trying to find the most token inefficient ways to build the best harness on the market sounds quite interesting to me, but not realistic.
Is doesn't even make sense, the limiting factor for Anthropic is GPU count, not profitability. They want more adoption at fixed GPU count which demands higher token efficiency.
+1 to a lot of what you said here, especially this:
> I used to tell myself that plan mode mitigated that, but I usually ended up mentally glossing over the generated plans anyway.
At a certain point I realized I far preferred delegating the first implementation pass to agents and reviewing the _code_ instead of a plan up front. If you had asked me this question ~2 years ago I'd think anyone would be insane to hand off discretion like this, but frontier models are just so _good_ nowadays.
Let's say you launch 10 working sessions in a day, would you rather:
* Review 10 plans, and _then_ review 10 PRs, and _then_ maybe adjust the approach on 1-2 and merge the other 8
* Review 10 PRs, and maybe adjust the approach on maybe 4 and merge the other 6
The first option just feels like needless attention for the sake of feeling in control; but the reality is that these models are becoming just as good if not better as us humans and our reckoning is here. Our codebase has enough linters, hooks, and guards such that generally the agent just follows our blessed patterns already, so what is plan mode actually doing beyond giving me a false sense of security? I'm still going to read the code anyways.
Yeah if anything Opus 5 taught me how little benchmarks mean to the actual real world performance of these models.
"Better" in every sense of the benchmarks and absolutely horrible results in my day-to-day work.
The verbosity, goal post moving, tendency to leave work unfinished, over focusing on unrealistic root causes when debugging, etc... etc...
It was the first time I actually pinned my models back because I just could not work with 5 for the price and performance it gave me. Hoping 5.5 is better this time around....
Absolutely love temporal, but pretty shocked to see they have a $12.55B valuation.... feels nuts?
We're using temporal as the foundation for agents running on our platform doing accounting work for clients, it's proven extremely effective and I love how durable workflows are within temporal.
+100 on the technology, but realizing they are also VC funded makes me a little more cautious when it comes to vendor lock in.
Sounds like you're contributing to your own narrative here. The only self-centered douche canoe of a comment I see in this thread is from you.
HN has its share of good & bad, but I've generally enjoyed talking to some of the people on this site; much more than sites like Reddit which imo fit your description much much better.
Yeah this article is quite shallow after having read it; delegating to a remote sub-agent sounds novel but how does it _actually_ perform?
I'm personally skeptical of optimizing for minimal token consumption, the closer to a vanilla setup I am the more confident I feel I'm always getting the best performance out of my models.
Just look at how JetBrains measured rtk and found that while an individual call saves tokens, agents on average perform *more* turns and use *more* tokens to accomplish one task[1]
I've almost entirely stopped using Opus 5, at least with Sonnet I know what i'm getting -- Fable for the complex stuff and Sonnet for the precision changes.
The verbosity of Opus 5 isn't even my issue, it's consistency. For every 10 tasks Opus 5 accomplishes, there's at least one task that Opus 5 does just an atrocious job of, or a debugging investigation that it just completely goes off the rails on.
I actually got hounded / insulted on a couple of my last answers for not providing timely responses to their comments on my answer and that was the last straw.