What it means is that a good CAD model is not just sticking stuff together in 3D space. Parametric flow means that a small number of measurements ripple through the design, and sketches and solids adapt. To do this right, it's easier to just understand the purpose and intent of the model, how it was manufactured, and draw from there.
One of the things you get from studying CAD diagrams — like the Solidworks exercises everyone works through — is that real world parts often have surprisingly few dimensioned constraints. A lot more emerges from geometry.
So you can look at a diagram and initially think "where the heck does it define this radius!?" and find that it never needs to, because that radius emerges from tangency, parallelism, perpendicularity etc., combined with fewer measurement constraints.
Specifying it as a measurement would therefore be overconstraint; it might lead to solids that are difficult/impossible to manufacture or erroneous when another measurement is changed.
The diagram will specify the actual driving measurements that come from the part's purpose, with the intent to adapt to different real-world requirements.
Any CAD tool that works from images is going to have to approximate, which will create over-complex models with to many measurements that are more fragile with respect to changes, whereas a design that has geometrical constraints in place that are logical will be simpler and more adaptable.
With functional parts, roughly, form follows function first, and manufacturability second. But you have to understand why, to be able to make a good part. Even (perhaps especially) with 3D printing. But not uniquely. For example, would this tool be able to understand why the draft angles on a plastic part were important, what determines the bend radius of a part that was made from pressed metal, etc.?
I must stress that I am an amateur. But my amateur skills have come from reading and learning about CAD and learning what makes a viable design.
(Sorry… this was a stupidly long answer but I am hungry and I figured I should try to blurt it out before I have to get up from my desk and cook. I've edited it a lot and cut out a bit that I will probably put in another comment later)
The Spark feature's UI isn't as good as the others.
For example, I'm not sure if it should prominently show recent workload, and unless I use MCP to manipulate files on my computer, local file manipulation isn't possible. Personally, I don't think it's going to be that useful.
Works correctly in opencode, but seems like they inject a system prompt:
Thinking:
> The user is asking what model I am. According to my system prompt, I'm powered by "deepseek-flash" with model ID "opencode-go/deepseek-flash".
>I'm powered by the model opencode-go/deepseek-flash.
The new meta model is fast and very cheap as well, and when used through OpenCode you get quite a lot of free tokens. But meta is also THE surveillance company, so probably also not a good choice in your case.
Is it? You're still putting a lot of thought and guidance into the agent's harness, the final code is just a tiny bit of that. It's like giving a junior developer final code vs explaining the whys and nuance. Which I'm not sure I want to give Meta
If someone shows me a picture of a haircut, or a dress and asked me if it would look good on them, I can't imagine it. My mind does not work like that. I just can't visually see it.
There's no way to win in that situation anyway - if you said "yes I think it'd look great!" and then they went and got their hair cut to match your suggestion but didn't like it, is it your fault for saying "yes"?
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