Comment by delaminator
Comment by delaminator 5 hours ago
Your assessment of Claude simply isn’t true.
Or Stackoverflow is really good.
I’m producing multiple projects per week that are weeks of work each.
Comment by delaminator 5 hours ago
Your assessment of Claude simply isn’t true.
Or Stackoverflow is really good.
I’m producing multiple projects per week that are weeks of work each.
Not the OP you're replying to, but I've put together quite a few projects using only LLMs, no hand crafted code anywhere (I couldn't do it!)
https://play.google.com/store/apps/details?id=com.blazingban...
https://play.google.com/store/apps/details?id=com.blazingban...
https://play.google.com/store/apps/details?id=com.blazingban...
Are they perfect? No probably not, but I wouldn't have been able to make any of these without LLMs. The last app was originally built with GPT-3.5.
There is a whole host of other non-public projects I've built with LLMs, these are just a few of the public ones.
At this point my prior is that all these 300/ns projects are some kind of internal tools, with very narrow scope and many just for a one-off use.
Which is also fine and great and very useful and I am also making those, but it probably does not generalize to projects that require higher quality standards and actual maintenance.
The problem I had that the larger your project gets, the more mistakes Claude makes. I (not a parent commenter) started with a basic CRUD web app and was blown away by how detailed it was, new CSS, good error handling, good selection and use of libraries, it could even write the terminal commands for package management and building. As the project grew to something larger Claude started forgetting that some code already existed in the project and started repeating itself, and worse still when I asked for new features it would pick a copy at random leaving them out of sync with eachother. Moving forward I've been alternating between writing stuff with AI, then rewriting it myself.
I also see a lot of this so I can't blame you for thinking it! See my other post about some projects build _only_ using LLMs.
They really should have been supplying at least a week worth of readymade "projects" to every freelance AI promoter out there to demonstrate x9000 AI productivity gains for the skeptics.
Because vibing the air about those gains without any evidence looks too shilly.
Claude has taught me so much about how to use jq better. And really, way more efficient ways of using the command line in general. It's great. Ironically, the more I learn the less I want to ask it to do things.
It’s not just good for small code bases. In the last six months I’ve built a collaborative word processor with its own editor engine and canvas renderer using Claude, mostly Opus. It’s practically a mini Google Docs, but with better document history and an AI agent built in. I could never have built this in 6 months by myself without Claude Code.
I think if you stick with a project for a while, keep code organized well, and most importantly prioritize having an excellent test suite, you can go very far with these tools. I am still developing this at a high pace every single day using these tools. It’s night and day to me, and I say that as someone who solo founded and was acquired once before, 10 years ago.
I'm just as much of an avid llm code generator fan as you may be but I do wonder about the practicality of spending time making projects anymore.
Why build them if other can just generate them too, where is the value of making so many projects?
If the value is in who can sell it the best to people who can't generate it, isn't it just a matter of time before someone else will generate one and they may become better than you at selling it?
The value is that we need a lot more software and now, because building software has gotten so much less time consuming, you can sell software to people that could/would not have paid for it previously at a different price point.
We don’t need more software, we need the right software implemented better. That’s not something LLMs can possibly give us because they’re fucking pachinko machines.
Here’s a hint: Nobody should ever write a CRUD app, because nobody should ever have to write a CRUD app; that’s something that can be generated fully and deterministically (i.e. by a set of locally-executable heuristics, not a goddamn ocean-boiling LLM) from a sufficiently detailed model of the data involved.
In the 1970s you could wire up an OS-level forms library to your database schema and then serve literally thousands of users from a system less powerful than the CPU in modern peripheral or storage controller. And in less RAM too.
People need to take a look at what was done before in order to truly have a proper degree of shame about how things are being done now.
Most CRUD software development is not really about the CRUD part. And for most framework, you can find packages that generate the UI and the glue code that ties it to the database.
When you're doing CRUD, you're spending most of the time with the extra constraints designed by product. It's dealing with the CRUD events, the IAM system, the Notification system,...
> That’s not something LLMs can possibly give us because they’re fucking pachinko machines.
I mostly agree, but I do find them useful for fuzzing out tests and finding issues with implementations. I have moved away from larger architectural sketches using LLMs because over larger time scales I no longer find they actually save time, but I do think they're useful for finding ways to improve correctness and safety in code.
It isn't the exciting and magical thing AI platforms want people to think it is, and it isn't indispensable, but I like having it handy sometimes.
The key is that it still requires an operator who knows something is missing, or that there are still improvements to be made, and how to suss them out. This is far less likely to occur in the hands of people who don't know, in which case I agree that it's essentially a pachinko machine.
Sure but these are likely just variations of existing things. And yet the quality is still behind the original
Would you mind sharing some of these projects?
I've found Claude's usefulness is highly variable, though somewhat predictable. It can write `jq` filters flawlessly every time, whereas I would normally spend 30 minutes scanning docs because nobody memorizes `jq` syntax. And it can comb through server logs in every pod of my k8s clusters extremely fast. But it often struggles making quality code changes in a large codebase, or writing good documentation that isn't just an English translation of the code it's documenting.