Definitely not my experience. No matter the model, if I'm working on something important (and there is little reason on working on something not important) I do care about correctness and understandability. While LLMs are great for throwaway one-time code (although that's also debatable), they cannot compete with code written by a seasoned professional. No matter how many times I've tried delegating writing code to LLMs I've always regretted it in a few months' time, because it is more buggy and I don't really know what is happening there.

The future is using LLMs for what they are good for. What that is still being found out. I've had great experience with LLMs reviewing the code (matches with Primagean's ~50% accuracy at finding bugs, which is really good) and for explaining unfamiliar concepts to me.

I firmly believe that the code itself needs to be 100% organic, and if it's not and you're relying on LLMs to generate tons of code, you haven't built enough abstraction to make it unnecessary.

After 18+ months of this, LLMs are incredible for getting rid of the work I hated most: Updating JIRA tickets, tedious little cleanup jobs, refactoring, etc. They are great at finding infosec issues.

They are also GREAT at writing code based on standards and patterns established by an actual human engineers. They are STILL trash at anything meaningfully complex from the ground up. I will go through hours of planning where I have to kick the hell out of its plans in ways that I don't think someone without a ton of real world experience could do. Even in the fancy new Fable models that remains true. They are not creative and any engineering worth doing requires creativity.

Some things to consider:

1: The quality of code varies widely from model to model. In Visual Studio Copilot, I get so-so code from GPT, great code from Claude 4.x, lousy results from Claude 5.x

2: "Novel work" is harder to get from an LLM than when it's following an example. For example, I can get great Blazor / HTML / css from an LLM (and then spend time iterating making small adjustments,) but if I'm writing a complicated DB query or implementing a novel algorithm, it's best to do by hand.

3: But, in the case of a novel algorithm or query, I get great results saying "please write unit tests for XXX". That alone makes me develop code twice as fast!

One thing that I find frustrating/disturbing about LLM generated code is that wrong stuff doesn't usually look wrong, so you almost have to review it even closer than what you'd review from a person. Like in the past when a developer was being sloppy, usually you could kind of tell superficially, but with LLM code it's usually well documented and superficially well structured, all while doing batshit insane things. Like today I noticed some code that it had written was just silently returning on errors without logging a warning or returning an error code. It "worked" but it was a major foot-gun!

You're moving too slow.

Over the last four days I've few shotted a 1:1 clone (and improvement) of Fal, OpenRouter, and Replicate in Rust. It's going to be open source.

I've lined up $300k of monthly commitments for it that land at launch. Might apply to YC with it.

Moving "organic" is too slow for the world today.

I can generate LLM code and it will be very stable long term, but you must be QA minded and non-stop testing, ask and make sure it generate maintainable code, watch for code smell etc. Maybe it won't match a very seasoned dev, but LLM's generate sht code because the dev allows it at the review stage.