alt Hacker News> I'm only using Opus at all because GPT-5.5 in the subscriptions only has a small (400k, but 258k effective) context window.
Do you find that makes a difference in your work? I've been using 5.5 high/xhigh to optimize and benchmark a C codebase, and just reading the initial code virtually fills the first context window. A session will auto-compact 5-15 times, but it seems to do okay in spite of that because the task is mainly focused on the latest window each time.
I think for programming the strength of GPT over Opus is winning here over the context window.
> I think for programming the strength of GPT over Opus is winning here over the context window.
On this, absolutely!
I more often use Opus for planning than for implementation. In those cases I really do need the very large context window, because the agent has to read in a bunch of my code base and a bunch of previous plan files and product context and such, to understand what we're talking about.
And then I need to go back and forth with it over a really extended period: getting into a bunch of details, asking it to load how things already work so that we can discuss options for evolution of those, etc.
For that kind of thing, compaction completely destroys its effectiveness because even if you try to serialize out all the decisions made in the conversation into a plan file, the agent still loses e.g. the plan files and code files that it's read in that are adding sharp edges to its understanding of the scope of what's being planned.
For implementation or something like what you're describing in the vein of benchmarking, often I can get away with compaction. Although even then, if the agent needs to have a lot "loaded" into its head, to implement something very, very subtle, complex or far-reaching, in those cases it can be really detrimental if it compacts.