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This has been my experience as well. However, it seems like the platforms like Cursor/Lovable/v0/et al are doing things differently
For example, this is Lovable’s leaked system prompt, 1550 lines: https://github.com/x1xhlol/system-prompts-and-models-of-ai-t...
Is there a trick to making gigantic system prompts work well?
"After extensive trial-and-error..." IMO, this is the difference between building deterministic software and non-deterministic software (like an AI agent). It often boils down to randomly making tweaks and evaluating the outcome of those tweaks.
> Encouraged structured thinking by forcing the AI to justify its findings first, significantly reducing arbitrary conclusions. Ah yes, because we know very well that the current generation of AI models reasons and draws conclusions based on logic and understanding... This is the true face palm.
Several studies have shown that we first make the decision and then we reason about it to justify it
In that sense, we are not much more rational than an LLM
[flagged]
Lessons.
"After extensive trial-and-error..." IMO, this is the difference between building deterministic software and non-deterministic software (like an AI agent). It often boils down to randomly making tweaks and evaluating the outcome of those tweaks.
1:Observation 2:Hypothesis 3:test 4:GOTO:1
This is every thing ever built ever
What is the problem exactly?
I think they skipped over a non-obvious motivating example too fast. On first glance, commenting out your CI test suite would be very bad to sneak into a random PR, and that review note might be justified. I could imagine the situation might actually be more nuanced (e.g. adding new tests and some of them are commented out), but there isn't enough context to really determine that, and even in that case, it can be wor…
If I reviewed that PR, absolutely I'd question why you're commenting that out. There better be a very good reason, or even a link to a ticket with a clear deadline of when it can be cleaned up/reverted
Lessons.
https://nolearnings.com/
Learnings might be the right choice here.
I wouldn't complain if the HN headline mutator were to replace "Learnings" with "lessons".
"After extensive trial-and-error..." IMO, this is the difference between building deterministic software and non-deterministic software (like an AI agent). It often boils down to randomly making tweaks and evaluating the outcome of those tweaks.
Afaik alchemists had a more reliable method than ... whatever this state of affairs is ^^