beefsack
Joined 14 years ago
Joined 14 years ago
I feel GTA 6 will be the last mainline GTA that we run on our local systems.
My group don't play competitively, we hop on for a bot bash once a week and the AI is a lot of fun to play against. I'm excited for them to finally release on Steam because that will lower the barrier to entry and increase exposure because the game definitely deserves success.
That doesn't guarantee maanHimself is the original author, but it's looking likely.
This happens to me more commonly in large projects (>100k LOC) and in those projects it seems to happen every few sessions. I feel this specific benchmark would be impacted by this more than the smaller contrived benchmarks.
"provider": {
"alibaba-token-plan": {
"models": {
"qwen3.8-max-preview": {
"limit": {
"context": 1048576,
"output": 65536
},
"modalities": {
"input": [
"text"
],
"output": [
"text"
]
},
"name": "Qwen3.8 Max Preview"
}
}
}
}Just like with real work, it's valuable to break down big tasks into small tasks that you can knock over in a single session. When a session does start getting too big, you just need to ask the agent to reply with a comprehensive handover report and paste it into a new session.
When leaders are both technical and open about these sorts of things it makes me feel like I can trust that they are invested in supporting and improving their products.
To be honest though, I've gotten to the point where I prefer the OpenCode UI. A big win for OpenAI is you can log in to your subscription in OpenCode, whereas this is not trivially achievable for a Claude subscription.
I was getting some really impressive cost efficiency today in OpenCode with the following:
* Main session agent: gpt-5.6-sol (high) via OpenAI subscription
* General purpose subagent: deepseek-v4-pro (high) via OpenCode Go subscription
* Using `obra/superpowers` for subagent driven workflows
* The main session only being allowed filesystem read permissions and everything else delegated
It was absolutely crunching through tasks without hitting the limit, and this combination is quite cost effective.GPT 5.6 was picking up on quality and functional issues from DeepSeek and having it resolve them cleanly, and I didn't even get close to my quotas whereas I can usually blast through them. I feel as people get more comfortable with subagents and mixing and matching models in their daily work, Anthropic's walled garden stance will start to hurt them.
Interested in remote Rust or Go jobs.
https://github.com/beefsack