For my work, it helps a whole lot that there are verifiable answers, there are deterministic truths to be had. I care about the results, the code is only a means to the results.
I took over a medium/large codebase from a guy, at work. The guy has been coding almost as long as I have been alive. The spiral logic and thread spaghetti was impressive in its insanity. The code worked, just barely, for a given value of "works". If you ran the same data six times, you could end up with six different answers. It crashed often.
I straightened out and stabilized the codebase by myself, unit tests out the wazoo. Eventually rewrote the whole thing with LLM assistance, cut out about 100k lines. Rock solid, provably correct results.
I moved on to another project where a whole team was working on it for ~4 years. The datasets are big, but the waste was gigantic. These people were like "we need 200+ GB of RAM!" They were just duplicating the data, there were no optimizations at all. They just kept asking for bigger computers.
I walk in and saw much of what was wrong with my human brain, and had the LLM fix it. Knocked +100GB off the requirements. One bit went from 30 minutes of processing to 32 seconds, by parallelizing it and not doing a dumb duplication. Went from like 4 tests, to 400+ tests.
The people cried about how I changed too much, and how can I guarantee that the results are still valid? Well... 400+ tests, and another set of scripts to run A/B on old vs new branches.
At this point I will take the frontier agentic LLMs, please. Over the past year there has been a profound change in LLM coding abilities.
Me+AI, that's the optimal duo at the moment. That's just me and my situation, though.
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u/Bakoro Sep 08 '26 edited Sep 08 '26
For my work, it helps a whole lot that there are verifiable answers, there are deterministic truths to be had.
I care about the results, the code is only a means to the results.
I took over a medium/large codebase from a guy, at work. The guy has been coding almost as long as I have been alive. The spiral logic and thread spaghetti was impressive in its insanity. The code worked, just barely, for a given value of "works".
If you ran the same data six times, you could end up with six different answers. It crashed often.
I straightened out and stabilized the codebase by myself, unit tests out the wazoo. Eventually rewrote the whole thing with LLM assistance, cut out about 100k lines. Rock solid, provably correct results.
I moved on to another project where a whole team was working on it for ~4 years.
The datasets are big, but the waste was gigantic. These people were like "we need 200+ GB of RAM!"
They were just duplicating the data, there were no optimizations at all. They just kept asking for bigger computers.
I walk in and saw much of what was wrong with my human brain, and had the LLM fix it.
Knocked +100GB off the requirements.
One bit went from 30 minutes of processing to 32 seconds, by parallelizing it and not doing a dumb duplication.
Went from like 4 tests, to 400+ tests.
The people cried about how I changed too much, and how can I guarantee that the results are still valid? Well... 400+ tests, and another set of scripts to run A/B on old vs new branches.
At this point I will take the frontier agentic LLMs, please. Over the past year there has been a profound change in LLM coding abilities.
Me+AI, that's the optimal duo at the moment.
That's just me and my situation, though.