Unfortunately I’ve used Claude and GPT models for a long time in a variety of harnesses and I agree with you and I think it’s the compaction.

For some reason, codex compaction is like black magic. I’ve never felt like I can just one one continuous thread with other models, Claude I carefully curate when I compact

Compacting at all is a mistake. With 1m context window there is no reason for a single task to require compaction.

Much better to spend tokens breaking the task into chunks, documenting and storing them durably, then executing each one in clean context and just /clear after.

It’s a similar concept to compaction, just planned in advance. Much much more effective, and doesn’t burn tokens and time (“wall-clock”, Claude) doing the compaction.

One interesting harness thing I saw Cursor do is to give the model access to the entire thread.

Even if it doesn't fit in the context window, the model can search through past turns and sanity check if something doesn't seem to be going right, or be prompted to follow an early message, "when starting on a new item, review the first message for how we should approach this"

Unlike other model/harness pairs, codex+gpt also passes an opaque encrypted artifact speculated to be an embedding representing the conversation back to the successor generation which is “denser” or at least higher fidelity than summarized text.

This is not an issue with Claude, but with Claude Code.

With swival.dev you can use long sessions without ever doing any manual compaction or reset, even with Claude models.