I think the thing I'm most excited about is the increase in _user prompting_.
If I give a poorly constrained/ambiguous prompt, I don't want the model one-shotting assumptions left and right.
The demos of Fable/GPT-6 are impressive, but "real AGI" should act more like a collaborator than either a peon or overachiever.
It's a tough balance to get right, and although this has been possible to achieve with additional prompting on existing models, I find that the agents often lean too hard into the "ask questions" mode.
Hopefully this model has the right balance, or at least better?
Anecdotal experiences from my external early testing of Astra: if you love Sol (like I do) and wished it was smarter at everything, but especially better at high-level tasks and discussions; I think you'll LOVE Astra.
Astra retains the best parts and overall 'grounded collaborator and executor' of Sol in my testing (harness: codex CLI); while being a significant leap in capabilities & higher-level thinking.
When you prompt it like a technical collaborator, I've found Astra to be extremely consistent in staying as a collaborator, and not being over-eager, over-achieving or doing work that you haven't asked it to.
When you ask it to one-shot something, or explicitly ask it to make decisions, it will of course make its own assumptions and decisions, and generally very well.
Astra is also excellent at instruction following and respecting the guidance and steers boundaries you have.
^OpenAI does not review, limit, or tell me what to say; opinions are my own experiences.
This is quite exciting. Sol for me has been the absolute best model yet. I find myself using it 95% of the time even though I have access to Fable. Is the speed the same as 5.6 sol?
Fellow excited. Sol has been revolutionary for me. It’s been the first time I’ve let a model “go ham” on a production code base and it actually worked, and also didn’t bankrupt my company in the process.
I’m far more excited for the trajectory that OpenAI has chosen. I’ve been listening to mates whose companies adopted Claude wholesale, only for their AI use to become a double digit percentage of their salary.
I get that AI is a force multiplier, but that level of expense isn’t a path to mass adoption.
Honestly, this feels like a real revolution now in a way that 90s kid never really experienced. We grew up with technological progression, we never experienced the obsolescence of skill.
The internet revolution made for more skills and innovation, it didn’t obsolete entire careers. My kids are almost certainly going to grow up knowing less but being capable of more.
Imagine being a 1950s “human calculator” on the dawn of a computer revolution. That’s what it feels like right now.
> "Imagine being a 1950s “human calculator” on the dawn of a computer revolution. That’s what it feels like right now."
My personal / family history is a real-world example of that evolution. My grandfather was a "computer", my father was a traditional "programmer" (lots of Perl), and I'm a SWE / frontend architect / budding "AI Engineer".
>>> The demos of Fable/GPT-6 are impressive, but "real AGI" should act more like a collaborator than either a peon or overachiever.
I don't really agree. The thing that makes Fable feel like an actual collaborator is its ability to sus out your real intent when you give ambiguous instructions. It's really good at it.
I watched some reviews today and came way with the impression that Astra is not better than Sol in this regard. You still have to be very specific with your instructions. For example, you can say "why is it not committed yet?" and it will give you an explanation and say it's actually ready to be committed. But it won't commit unless you explicitly say so.
That sounds like a very tedious way of working with AI agents, but I understand some people want a high level of control.
This is one of those things that won't ever be "solved" as people just want different things here, hence we can steer the models with the system prompt.
I'm mostly the same as you, I don't want the model to assume things, or act on implicit "directions". But then also, sometimes I do, and I myself might not always know when what approach is best.
Indeed some people think they want a machine guessing at your intentions and acting upon that guess. Those people
Are wrong in at least 2 directions: that it is what they want, and their implicit assumption that it could possibly be safe.
Indeed, I don’t ask rhetorical questions to an AI. They are of doubtful use when talking verball ly to a human, less good in online discussions, and totally unnecessary for agents.
Interesting. I actually prefer when agents don't commit on my behalf unless I explicitly say so, I even had to add a custom instruction for Claude to stop doing it (Codex never does it). Even if I don't read all the code line-by-line, I at least want to see the changes at glance and commit myself. Git Fork[0] is a great tool for that, by the way.
In general, I don't like when I have to prompt models to NOT do something. It's probably difficult for the AI companies to get this right, they should understand ambiguity but still not over-do simple instructions.
> For example, you can say "why is it not committed yet?" and it will give you an explanation and say it's actually ready to be committed. But it won't commit unless you explicitly say so.
Well thank God, because that's the correct behavior. When you wanted to commit you can literally just say "commit" and nothing else.
Imagine if you asked it "you didn't delete my production database did you?"... And then it deletes your production database
This is spot on. A collaborator is exactly what real AGI is. It will figure out the perfect questions to ask, in the perfect order, by intelligently assessing the entire solution and problem space upfront, so when you leave it to go off on its own it isn't making stupid decisions for you.
They really need to make this work in Codex. Claude Code has had a multi-select refinement tool since forever.
> They really need to make this work in Codex. Claude Code has had a multi-select refinement tool since forever.
I think this already exists in Codex? If you use "/plan" and something is unclear or ambiguous, Codex will ask you and present choices, and let you enter your own custom answer. Then it'll iterate like this until the plan is clear and ambiguous. Isn't this what you're talking about? If so, it has existed for a long time in Codex.
Overall I agree with you though, all the models currently don't have the right hunches nor the right approach about when things are clear enough or not.
That balance probably depends on the human, and the context. If you are a beginner in a field the model should not assume you know what you are doing. On the other hand, for an expert it should try to work out what you mean with your vaguely worded order.
What I think should happen is that it should update its memory with notes on the proficiency level of the user, so it gets the balance right over time.
This is a problem if you allow your kids to use your ChatGPT account for homework (and silly pictures), like I do.
> What I think should happen is that it should update its memory with notes on the proficiency level of the user, so it gets the balance right over time.
Which can also involve just asking for the users level of experience
and that's exactly what most people don't want. they want some ultra-intelligent being that can do marvelous things, and they can claim the credit on it
If I give a poorly constrained/ambiguous prompt, I don't want the model one-shotting assumptions left and right.
The demos of Fable/GPT-6 are impressive, but "real AGI" should act more like a collaborator than either a peon or overachiever.
It's a tough balance to get right, and although this has been possible to achieve with additional prompting on existing models, I find that the agents often lean too hard into the "ask questions" mode.
Hopefully this model has the right balance, or at least better?