161–170 of 481 posts
Earlier quoted context omitted.
"Really does not sound like that from your description. It sounds like coaching a noob, which is a lot of work in itself." And if this is true, you will have to coach AI each time whereas a person should advance over time.
The AI in this example is 1/100 the cost.
AI produces code that often looks really good, at a pace quicker than you can read it. It can be really, really hard to tell when what it's producing is a bag of ** and it's leading you down the garden path. I've been a dev for 20 years (which isn't to imply I'm any good at it yet) and it's not uncommon I'll find myself leaning on the AI a bit too hard and then you realise you've lost a day to a pattern that wasn't r…
If you have good tests and a good sense for design and you know how to constrain and direct the AI, you can avoid a lot of boring work. That is something.
The best code I've written with an LLM has been where I architect it, I guide the LLM through the scaffolding and initial proofs of different components, and then I guide it through adding features. Along the way it makes mistakes and I guide it through fixing them. Then when it is slow, I profile and guide it through optimizations. So in the end, it's code that I know very, very well. I could have written it but it…
>... it doesn't matter so much that you know every detail of the implementation, as long as it is validated. What makes me nervous is when we generate both the implementation and the test cases. In what sense is this validation?
Attempting to guide it to fixing the errors just introduced novel errors that it didn't make the first time around.
This is not what I signed up for.
Earlier quoted context omitted.
There was one study that said that in a specific setting and was amplified heavily on forums by anti-AI people. There have been many more studies showing productivity gains across a variety of tasks that preceded that one. That study wasn't necessarily wrong about the specific methodology they had for onboarding people to use AI. But if I remember correctly it was funded by an organization that was slightly skeptical…
which studies show this?
AI coding assistant trial: UK public sector findings report: https://www.gov.uk/government/publications/ai-coding-assista... - UK government. "GDS ran a trial of AI coding assistants (AICAs) across government from November 2024 to February 2025. [...] Trial participants saved an average of 56 minutes a working day when using AICAs"
Human + AI in Accounting: Early Evidence from the Field: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5240924 - "We document significant productivity gains among AI adopters, including a 55% increase in weekly client support and a reallocation of approximately 8.5% of accountant time from routine data entry toward high-value tasks such as business communication and quality assurance."
OECD: The effects of generative AI on productivity, innovation and entrepreneurship: https://www.oecd.org/en/publications/the-effects-of-generati... - "Generative AI has proven particularly effective in automating tasks that are well-defined and have clear objectives, notably including some writing and coding tasks. It can also play a critical role for skill development and business model transformation, where it can serve as a catalyst for personalised learning and organisational efficiency gains, respectively [...] However, these potential gains are not without challenges. Trust in AI-generated outputs and a deep understanding of its limitations are crucial to leverage the potential of the technology. The reviewed experiments highlight the ongoing need for human expertise and oversight to ensure that generative AI remains a valuable tool in creative, operational and technical processes rather than a substitute for authentic human creativity and knowledge, especially in the longer term.".
Earlier quoted context omitted.
> Really does not sound like that from your description. It sounds like coaching a noob, which is a lot of work in itself. Even if you do it by yourself, you need to do the same thinking and iterative process by yourself. You just get the code almost instantly and mostly correctly, if you are good at defining the initial specification.
This. You _have_ to write the spec. The result is that instead of spending X units of time on spec and THEN y units of time on coding, you get the whole thing in x units of time AND you have a spec. The trick is knowning where the particular LLM sucks. I expect in a short amount of time there is no productivity gain but when you start to understand the limitations and strengths - holey moley.
It's more like x units of time thinking and y units of times coding, whereas I see people spend x/2 thinking, x typing the specs, y correcting the specs, and y giving up and correcting the code.
The best code I've written with an LLM has been where I architect it, I guide the LLM through the scaffolding and initial proofs of different components, and then I guide it through adding features. Along the way it makes mistakes and I guide it through fixing them. Then when it is slow, I profile and guide it through optimizations. So in the end, it's code that I know very, very well. I could have written it but it…
Ya the early "studies" that said AI would benefit low skill more than senior never seem grounded in reality. Coding with AI is like having a team of juniors that can complete their assignments in a few minutes instead of days. The more clear your instructions, the closer it is to what you wanted, but there are almost always changes needed. Unfortunately it really does make the junior dev position redundant (although…
The elephant in the room being that if you aren’t senior enough to have written the code you’ll probably run into a catastrophic bug that you are incapable of fixing (or prompting the LLM to fix) very very quickly.
Really it’s just the next iteration of no-code hype where people dream of building apps without code, but then reality always come back to the fact that the essential skill of programmers is to understand and design highly structured and rigid logical systems. Code is just a means of specification. LLMs make it easier to leverage code patterns that have been written over and over by the hundreds of thousands of programmers that have contributed to its training corpus, but they can not replace the precision of thought needed to make a hand-wavy idea into a concrete system that actually behaves in a way that humans find useful.
Earlier quoted context omitted.
> I could have written it but it would have taken me about 3x longer when all is said and done. Really does not sound like that from your description. It sounds like coaching a noob, which is a lot of work in itself. Wasn’t there a study that said that using LLMs makes people feel more productive while they actually are not?
Sure it’s a lot of work, but the noob in question has all the internet knowledge and can write multiples times faster than a human for a fraction of the costs. This is not about an individual being more productive, this is about business costs. Long term we should still hire and train juniors obviously, but short term there is lot of pressure to not do it as it makes no sense financially. Study or not the reality is…