Tangential (but topical in that "The threat is comfortable drift toward not understanding what you're doing" is also on the front page):
Is the generated python code in the example wrong?
The prompt
> Develop a Python function that removes any falsey values from a list. Return the modified list without creating a new one.
Is answered with list comprehension, which makes a new list and leaves the original unmodified (never mind that the *args input necessarily can't be a modifiable list?)
def remove_falsey_values(*args): return [val for val in args if val]
Whereas I'd expect something like
def remove_falsey_values(l):
for i in reversed(range(len(l))):
if not l[i]: l.pop(i)
# returned list is linked to input l
return l
a = [1, 0, False, 'foo']
x = remove_falsey_values(a)
x[0] = 2
print(a) # [2,'foo']
It doesn't fit the requirement to modify the list in place, but the prompt itself contradicts the requirements by asking explicitly for the implementation to use *args and a list comprehension.
Ahh I didn't see the full original prompt -- it's overflowing into a horz scroll for me. I thought it was the "critique loop" that injected the *args requirement. I guess garbage in, garbage out. Still unfortunate example to use.
Oh I wouldn't be surprised. This is a sample from one of the OSS code datasets I'd used, which are all generated synthetically using LLMs. Data is indeed the moat.
Absolutely! And the list.pop version is multiple orders of magnitude slower. But I took the prompt to be asking for in-place modification of the existing list. Comprehension does not do that.
> This is a library showing you how to train your own Claude Code end-to-end.
What does it even mean?
Claude Code is a so called "harness" - a thing that builds a context for LLMs, calls LLMs, executes tool calls etc. It uses various Anthropic models under the hood.
It can also use other models AFAIK.
It cannot be "trained".
Sorry if this comment sounds nitpicky, I'm just annoyed by the imprecise use of terminology.
26 comments
Is the generated python code in the example wrong?
The prompt
> Develop a Python function that removes any falsey values from a list. Return the modified list without creating a new one.
Is answered with list comprehension, which makes a new list and leaves the original unmodified (never mind that the *args input necessarily can't be a modifiable list?)
Whereas I'd expect something likeWhy would people want to spend $200 to train a coding model when there are free coding models?
> This is a library showing you how to train your own Claude Code end-to-end.
What does it even mean?
Claude Code is a so called "harness" - a thing that builds a context for LLMs, calls LLMs, executes tool calls etc. It uses various Anthropic models under the hood.
It can also use other models AFAIK.
It cannot be "trained".
Sorry if this comment sounds nitpicky, I'm just annoyed by the imprecise use of terminology.
https://github.com/Nano-Collective/nanocoder
Any practitioners can elaborate?