monoid73

6 ms·

1.
by monoid73 1y ago
for the hybrid workflows, curious how do you decide which parts need AI reasoning vs can be hardcoded? is it adaptive or manual config?
2.
Show HN: Open Operator Evals – real-world benchmarks for LLM web agents(github.com)
3 points by monoid73 1y ago|1 comments
3.
by monoid73 1y ago
Another one? People saw that 3B windsurf money.
4.
by monoid73 1y ago
think the visa hurdle is the big one. even if you have a strong background, a lot of companies hesitate unless they already have an immigration pipeline set up. another angle could be looking for remote roles at US companies first, then try
5.
by monoid73 1y ago
I think the UX of chatgpt works because it's familiar, not because it's good. Lowers friction for new users but doesn't scale well for more complex workflows. if you're building anything beyond Q&A or simple tasks, y
6.
by monoid73 1y ago
funny enough, i started noticing em dashes mostly through using GPT. wasn’t really part of my writing before, but now i find them super useful for managing rhythm and flow. definitely earned their place — not because LLMs use them, but bec
7.
by monoid73 1y ago
this is one of the more compelling "LLM meets real-world tool" use cases i've seen. openSCAD makes a great testbed since it's text-based and deterministic, but i wonder what the limits are once you get into more complex
8.
by monoid73 1y ago
exactly. hindsight bias makes it really hard to separate genuine inference from subtle prompt leakage. even framing the question can accidentally steer it toward the right answer. would be interesting to try with completely synthetic proble
9.
by monoid73 1y ago
same here. brew’s been great historically but it’s gotten bloated and kinda slow. curious to see if sapphire can keep things lean without sacrificing compatibility.
10.
by monoid73 1y ago
yeah, that'd b nice, some kind of self-bootstrapping system where you start with a strong cloud model, then fine-tune a smaller local one over time until it’s good enough to take over. tricky part is managing quality drift and deciding