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0 pointsDumbledumb5h ago0 comments

This blog post is full of small inconsistencies that make it read like a low quality SEO piece.

> We also extract a shared context file (shared-mr-context.txt) from the coordinator's prompt and write it to disk. Sub-reviewers read this file instead of having the full MR context duplicated in each of their prompts. This was a deliberate decision, as duplicating even a moderately-sized MR context across seven concurrent reviewers would multiply our token costs by 7x.

No, it would not, because neither is the prompt of the subagent 100% of its token usage, nor will the "shared-mr-context.txt" which is then being read have a size of zero compared to the creation of this shared context.

> You don't need seven concurrent AI agents burning Opus-tier tokens to review a one-line typo fix in a README.

Yeah, well you wouldn't have anyways. Earlier in the post it says that Opus is "exclusively for the Review Coordinator".

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DumbledumbOP5h ago

Also this seems plain wrong. Input token caching has now idea whether you @include the file or copy the contents into the prompt. That is handled entirely by opencode and, all else being equal, has no bearing on the cache ability of a trace.

> Our cache hit rate sits at 85.7%, which saves us an estimated five figures compared to what we would pay at full input token pricing. This is partially thanks to the shared context file optimisation — sub-reviewers reading from a cached context file rather than each getting their own copy of the MR metadata, but also by using the exact same base prompts across all runs, across all merge requests.

fg1373h ago

Looks like they need some sort of agent to review their blog posts as well.

j / k navigate · click thread line to collapse

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DumbledumbOP5h ago

fg1373h ago

Looks like they need some sort of agent to review their blog posts as well.

j / k navigate · click thread line to collapse