101–110 of 219 posts
I think if you are not seeing reasonable performance in your agent loops as of 5.5, it's likely there is a deficit with how the loop, prompt or tools interact with the environment.
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I feel like listening to Theo about anything technical is like consulting a Labrador retriever for advice on quantum physics. Every time I've ever seen one of his videos it's pretty clear he has very little understanding of development or engineering. I first became aware of him from his early "unit tests are a waste of time" stuff, and it seems his skillset is building a personal brand. Fair play, he's clearly talen…
> it's pretty clear he has very little understanding of development or engineering I cannot prove it but I have a feeling that you may be conflating "he clearly has different opinions on things I consider non-negotiable" to "he doesn't know what he's talking about". I also watched a lot of his videos. I wildly disagree with him a lot of times, but he has his reasoning, and I can see (and verify!) that those ideas are…
That's his motivation, influencing. Not teaching.
I'm not so against him as the previous commentor but I feel basically all YouTubers who have succeeded in building a brand have the same problem. They have to present their opinions as unassailable truth, they can't allow nuance. Within reason of course, they also have to play the game of appearing considerate and understanding of other people but it will always boil down to proving they are the real experts, their ultimate goal is always to get you watching more of their content.
If they don't do this, they appear less trustworthy and their brand wouldn't have grown as much as it did. They might genuinely have some expertise to share, and even contrary or downright wrong takes could teach us something if they were only presented in a way that encourages critical thinking. But as the person above said, their real deep expertise is in brand building.
Coding with AI it feels like if you're not using the best model then you're possibly missing out - creating less capable, maintainable, just plain 'good' code. Why waste time using anything less than the best and cleaning up the mess later on. This is why I feel like local models and Chinese models aren't taking off (and Gemini/Grok) - they work, but they're plain just not as good as OpenAI/Anthropic. If you have the…
That depends entirely on how you're using AI. If you're getting it to do all the hard thinking, then sure using the best model is probably always going to be better. But it's also going to be expensive. Using cheaper models and using your skills and expertise from the pre-AI era can get you working just as fast. You've gotta be more specific about the work you need doing. It's less "vibes" based, but they're still ef…
I’d describe it as something between Sonnet and Opus.
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Do you have a source for this? I'm pretty sure responses api is only there to obfuscate reasoning, but that they're still keeping reasoning traces in the backend.
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I'm most curious about whether OpenAI finally taught its models how to design interfaces. They have been behind the other labs in this area for what feels like ages.
I know a few of my comments are related to this, but these new names are horrible. Why introduce ANOTHER layer of confusion and drop the mini, nano suffixes that people got used to? How does this go through so many layers of management at a trillion dollar company without who has a say raising this? I simply can't believe how stupid the naming scheme from OpenAI was and continues to be even after they acknowledged it…
I know a few of my comments are related to this, but these new names are horrible. Why introduce ANOTHER layer of confusion and drop the mini, nano suffixes that people got used to? How does this go through so many layers of management at a trillion dollar company without who has a say raising this? I simply can't believe how stupid the naming scheme from OpenAI was and continues to be even after they acknowledged it…
Sounds like the source of your problem, right there.
Earlier quoted context omitted.
Do you have a source for this? I'm pretty sure responses api is only there to obfuscate reasoning, but that they're still keeping reasoning traces in the backend.
I work at OpenAI and can confirm that's correct: reasoning tokens are discarded after each new user turn (though not after each message or tool call). Our docs show a diagram here: https://developers.openai.com/api/docs/guides/reasoning > Input and output tokens from each step are carried over, while reasoning tokens are discarded. Keeping reasoning tokens around is better for caching and for remembering past insight…
This is something I never understood. Why the reasoning is not included until the context is full, then the reasoning stripped optionally to allow the conversation to continue. and only then when its truly full offer a compaction. Was it to optimize caching? Well I guess it doesn't matter now that you hinted that this choice was made because of prior limitations and may change very soon
Thoughts[^0] from Theo, who had early access: > It's a damn good model. Not quite as "smart" as Fable, but it is incredibly capable. Fixed all the problems I had with GPT-5.5. > It is incredibly determined. Will run for a day without even using a /goal. It understands subagents incredibly well and is great at orchestrating. It's super pleasant in use cases like OpenClaw and Hermes Agent. It knows iOS dev incredibly w…
> Not quite as "smart" as Fable, but it is incredibly capable. THIS IS BECAUSE GPT-5.6 SOL IS... just a more posttrained version of GPT-5.5, not a brand new bigger model than GPT-5.5. It's not like how Mythos is bigger than Opus. OpenAI switching to Sol/Terra/Luna renaming is just a way to rip off people and charge more usage for the same sized model. GPT-5.6 --------> GPT-5.6 Sol GPT-5.6-mini ---> GPT-5.6 Terra GPT-…
I know a few of my comments are related to this, but these new names are horrible. Why introduce ANOTHER layer of confusion and drop the mini, nano suffixes that people got used to? How does this go through so many layers of management at a trillion dollar company without who has a say raising this? I simply can't believe how stupid the naming scheme from OpenAI was and continues to be even after they acknowledged it…
Whereas Sol/Luna/Terra reads more like "GPT for hard/medium/basic problems".