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Comment by AdieuToLogic

8 days ago

> You appear to be confusing "produce working code" with "exclusively produce working code".

The confusion is not mine own. From the article cited:

  Dave Treadwell, Amazon's SVP of e-commerce services, told 
  staff on Tuesday that a "trend of incidents" emerged since 
  the third quarter of 2025, including "several major" 
  incidents in the last few weeks, according to an internal 
  document obtained by Business Insider. At least one of 
  those disruptions were tied to Amazon's AI coding assistant 
  Q, while others exposed deeper issues, another internal 
  document explained.
  
  Problems included what he described as "high blast radius 
  changes," where software updates propagated broadly because 
  control planes lacked suitable safeguards. (A control plane 
  guides how data flows across a computer network).

It appears to me that "Amazon's SVP of e-commerce services" desires producing working code and has identified the ramifications of not producing same.

4 comments

AdieuToLogic

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simonw  8 days ago

That's why I'm writing a guide about how to use this stuff to produce good code.

  • AdieuToLogic  6 days ago

    > That's why I'm writing a guide about how to use this stuff to produce good code.

    Consider the halting problem[0]:

      In computability theory, the halting problem is the problem
  of determining, from a description of an arbitrary computer
  program and an input, whether the program will finish
  running, or continue to run forever. The halting problem is
  undecidable, meaning that no general algorithm exists that
  solves the halting problem for all possible program–input
  pairs.

    Essentially, it identifies that mathematics cannot prove an arbitrary program will or will not terminate based on the input given to it. So if math cannot express a solution to this conundrum, how can any mathematical algorithm generate solutions to arbitrary problems which can be trusted to complete (a.k.a. "halt")?

    Put another way, we all know "1 + 2 = 3" since elementary school. Basic math assumed everyone knows.

    Imagine an environment where "1 + 2" 99% of the time results in "3", but may throw a `DivisionByZeroException`, return NaN[1], or rewrite the equation to be "PI x r x r".

    Why would anyone trust that environment to reliably do what they instructed it to do?

    0 - https://en.wikipedia.org/wiki/Halting_problem

    1 - https://en.wikipedia.org/wiki/NaN

    • simonw  6 days ago

      I find the challenge of using LLMs to usefully write software despite their non-deterministic nature to be interesting and deserving of study.

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