Honestly, its mind boggling. Am I the worst prompter ever?
I have three python files (~4k LOC total) that I wanted to refactor with help from Claude 4 (Opus and Sonnet) and I followed Reed Harper's LLM workflow...the results are shockingly bad. It produces an okay plan, albeit full of errors, but usable with heavy editing. In the next step though, most of the code it produced was pretty much unusable. It would've been far quicker for me to just do it myself. I've been trying to get LLMs on various tasks to help me be faster but I'm just not seeing it! There is definitely value in it in helping to straighten out ideas in my head and using it as StackOverflow on roids but that's where the utility starts to hit a wall for me.
Who are these people who are "blown away" by the results and declaring an end to programming as we know it? What are they making? Surely there ought to be more detailed demos of a technology that's purported to be this revolutionary!?
I'm going to write a blog post with what I started with, every prompt I wrote to get a task done and responses from LLMs. Its been challenging to find a detailed writeup of implementing a realistic programming project; all I'm finding is small one off scripts (Simon Willison's blog) and CRUD scaffolding so far.
I couldn't agree more. This has been my exact experience.
Like you I'll probably write a blog post and show, prompt by prompt, just how shockingly bad Claude frequently is. And it's supposed to be one of the best at AI assisted coding, which mean the others are even worse.
That'll either convince people, match their experiences, or show me up to be the worst prompter ever.
I think you're supposed to let the AI write the bad python code and then do the refactoring yourself. No way I'm letting the AI make changes to 150 files with tons of cross-concerns when I don't even fully understand it all myself unless I dig into the code.
That being said copilot and chatgpt have been a 40% productivity boost at least. I just write types that are as tightly fitting as possible, and segregate code based on what side effects are going to happen, stub a few function heads and let the LLM fill in the gaps. I'm so much faster at coding than I was 2-3 years ago. It's like I'm designing the codebase more than writing it.
I have three python files (~4k LOC total) that I wanted to refactor with help from Claude 4 (Opus and Sonnet) and I followed Reed Harper's LLM workflow...the results are shockingly bad. It produces an okay plan, albeit full of errors, but usable with heavy editing. In the next step though, most of the code it produced was pretty much unusable. It would've been far quicker for me to just do it myself. I've been trying to get LLMs on various tasks to help me be faster but I'm just not seeing it! There is definitely value in it in helping to straighten out ideas in my head and using it as StackOverflow on roids but that's where the utility starts to hit a wall for me.
Who are these people who are "blown away" by the results and declaring an end to programming as we know it? What are they making? Surely there ought to be more detailed demos of a technology that's purported to be this revolutionary!?
I'm going to write a blog post with what I started with, every prompt I wrote to get a task done and responses from LLMs. Its been challenging to find a detailed writeup of implementing a realistic programming project; all I'm finding is small one off scripts (Simon Willison's blog) and CRUD scaffolding so far.