I’m probably not arguing with you, and I’m not trying to regardless. You seem like you have tried this, watched it happen, go “huh, neet!” And then get it to take the next step in whatever you were doing in the first place only to find out you didn’t provide adequate requirements for your config.
only to find out you didn’t provide adequate requirements for your config.
Every software development project, ever.
Review your requirements before starting development. Review them again after each phase of development. Address inadequacies, conflicts, ambiguities whenever you find them.
AI is actually helpful in this process - not so much knowing what to choose to do, but pointing out the gaps and contradictions it can be helpful.
I am a senior programmer. LLMs are amazing - I know exactly what I want, and I can ask for it and review it. My productivity has gone up at least 3-fold, with no decrease in quality, by using LLMs responsibly.
But it seems to me that some people on social media just can’t imagine using LLMs in this way. They just imagine that all LLM usage is vibe coding, using the output without understanding or review. Obviously you are very unlikely to create any fundamentally new solutions if you only use LLMs that way.
only to find out you didn’t provide adequate requirements for your config.
Senior programmer. I know exactly what I want. My requirement communicated to the LLM are precise and adequate.
What I find LLMs doing for my software development is filling in the gaps. Thorough documented requirements coverage, unit test coverage, traceability, oh you want a step by step test procedure covering every requirement? No problem. Installer scripts and instructions. Especially the stuff we NEVER did back in the late 1980s/early 1990s LLMs are really good at all of that.
Nothing they produce seems 100% good to go on the first pass. It always benefits from / usually requires multiple refinements which are a combination of filling in missing specifications, clarifying specifications which have been misunderstood, and occasionally instructing it in precisely how something is expected to be done.
A year ago, I was frustrated by having to repeat these specific refinement instructions on every new phase of a project - the LLM coding systems have significantly improved since then, much better “MEMORY.md” and similar capturing the important things so they don’t need to be repeated ALL THE TIME.
On the other hand, they still have their limits and in a larger recent project I have had to constantly redirect the agents to stop hardcoding every solution and make the solution data driven from a database.
Never use it blind, and like I more or less said above: if you’re taking the first response you’re using it wrong. I go at it expecting everything it says to be 80% right, finding that 20% telling it what’s wrong with it, then getting to 96% right - if the 4% off target is a problem, refine again…
Where it excels for me is generating long detailed (mind numbing) point by point descriptions of things - the kind of documents you can skim to see where they are right and wrong but would fall asleep or have a case of terminal ADHD before finishing creating them on your own.
If you are capable of giving good directions…
I’m probably not arguing with you, and I’m not trying to regardless. You seem like you have tried this, watched it happen, go “huh, neet!” And then get it to take the next step in whatever you were doing in the first place only to find out you didn’t provide adequate requirements for your config.
Every software development project, ever.
Review your requirements before starting development. Review them again after each phase of development. Address inadequacies, conflicts, ambiguities whenever you find them.
AI is actually helpful in this process - not so much knowing what to choose to do, but pointing out the gaps and contradictions it can be helpful.
Well, yes, that is a central point.
I am a senior programmer. LLMs are amazing - I know exactly what I want, and I can ask for it and review it. My productivity has gone up at least 3-fold, with no decrease in quality, by using LLMs responsibly.
But it seems to me that some people on social media just can’t imagine using LLMs in this way. They just imagine that all LLM usage is vibe coding, using the output without understanding or review. Obviously you are very unlikely to create any fundamentally new solutions if you only use LLMs that way.
Senior programmer. I know exactly what I want. My requirement communicated to the LLM are precise and adequate.
What I find LLMs doing for my software development is filling in the gaps. Thorough documented requirements coverage, unit test coverage, traceability, oh you want a step by step test procedure covering every requirement? No problem. Installer scripts and instructions. Especially the stuff we NEVER did back in the late 1980s/early 1990s LLMs are really good at all of that.
Nothing they produce seems 100% good to go on the first pass. It always benefits from / usually requires multiple refinements which are a combination of filling in missing specifications, clarifying specifications which have been misunderstood, and occasionally instructing it in precisely how something is expected to be done.
A year ago, I was frustrated by having to repeat these specific refinement instructions on every new phase of a project - the LLM coding systems have significantly improved since then, much better “MEMORY.md” and similar capturing the important things so they don’t need to be repeated ALL THE TIME.
On the other hand, they still have their limits and in a larger recent project I have had to constantly redirect the agents to stop hardcoding every solution and make the solution data driven from a database.
I were simply unable to convince Codex to split a patch into separate git commits in a meaningful way. There are things that just doesn’t work.
Still useful for lots of stuff. Just don’t use it blind.
Never use it blind, and like I more or less said above: if you’re taking the first response you’re using it wrong. I go at it expecting everything it says to be 80% right, finding that 20% telling it what’s wrong with it, then getting to 96% right - if the 4% off target is a problem, refine again…
Where it excels for me is generating long detailed (mind numbing) point by point descriptions of things - the kind of documents you can skim to see where they are right and wrong but would fall asleep or have a case of terminal ADHD before finishing creating them on your own.