I'm pretty conservative when it comes to clearing the context, and I also tend to provide the right files to work on (or at least the right starting point).

I had seen prior to using the model that it starts producing much worse results when the context used is larger, so my usage style probably helps getting better results. I work like this with Claude Code anyway, so it wasn't a big change.

OpenCode picked up my CLAUDE.md files and skills straight away, and I got similar performance to Opus 4.6.

Raised with support immediately, after being told a human would look at it I've not been able to get anything further.

I feel like for the first time in our lives we might have seen peak technology for the next few years. Everyone is going to have to make do instead of depending on ever increasing performance.

You put in real work to understand the business landscape and typical pain points. With AI, implementing solutions has become much easier but knowing what the problems are and how to solve them hasn't.

Comments URL: https://news.ycombinator.com/item?id=47485767

Points: 3

# Comments: 0

"Why are you using Go? Rust is best! You should be using that!" "Don't use AWS CDK, use Terraform! Don't you know anything?"

Simple suggestion: logo should be a cow and and orc to match how I originally read the product name.

AIUI everything relies on TSMC (Amazon and Google custom hardware included), so they're still having to pay to get a spot in the queue ahead of/close behind nvidia for manufacturing.

From my non-production experiments with it, the main limitation is that you can only retrieve up to 30 top_k results, which means you can't use it with a re-ranker, or at least not as effectively. For many production use cases that will be a deal breaker.