Comment by physicallyIllfr
12 hours ago
Lighting my codebase on fire at the speed of light. Like microwaving the spaghetti.
I genuinly only see these speeds being useful for customer service/transactional workflows. Of which much smaller models can do the job (but those dont make tons of money for companies like Cerebras that need to pay off massive amounts of debt).
Nobody needs to code at 600 words per second. Using a 100tps model for an hour or so will leave you with 4-8hrs of code review and revision work.
Human code review? What is this, 2025? The modality today is write with one LLM, review by a different one, (important: two different model families will catch errors one series won't) then deploy right to production.
Yeah, idk. I work on serious things. Thats not how I do things. Not everything is webdev hobby projects. There's basically no instance where offloading your code review to an llm is acceptable behavior, except maybe for a one off tool you need personally.
> then deploy right to production
And when things go south, you blame AI?
I would be very curious to see how you explain it to your customers.
Is it going to sound similar to this?
> You see, our well-meaning AI-generated code has caused all your data to be permanently deleted. In case you are confused as to who to blame, we would like to clarify that we did not write, nor review the code. So we cannot possibly bear any responsibility for its mistakes. The responsibility lies with the LLMs, not us. We have already fired the LLM which did the coding and the review. And we are already using their main competitors. Hopefully that settles your concern with the quality of our service and we are looking to have you on board of our next products.
> And when things go south, you blame AI?
This seems to work well enough for people who deploy cloud instances without redundancy to us-east-1 then blame AWS when there's an outage. I say this somewhat unironically because if one pushes the "move fast and break things" slider all the way to the right then they're necessarily assuming that type of risk. Of course some people will try to have their cake and eat it too [1] as regards velocity and quality but that's a separate discussion.
[1] I've never understood this idiom because if one isn't in possession of their cake before eating it then they're eating stolen cake which is a decidedly anti-social activity and orthogonal to the point of the saying. It should be "eat their cake and keep it too" or something.
And if you tell the reviewer the author is a competitors model it becomes extra snarky and vigilant. Then give the review results to the author and tell it it's from the competition and it will also become slightly outraged.
No you dont need to code at 600 w/s BUT at those speeds, you can start doing things like asking multiple different agents the same question and picking the best solution each time without noticing the lag.
So 3x the code review lol. This is similar in concept to how a slot machine leta you choose 1x, 3x 6x lol
> Nobody needs to code at 600 words per second.
I do. I used to use haiku for the speed. Now its just as slow as the rest. Speed is my #1 ranking of how good a model is
I prefer a fast model too, but you cannot get more done just because its faster. You just get to the human parts a bit faster. Code review, revision ect.
I don't even notice the LLM speed or latency. I think we are as far apart in technique as it gets.
What is your workflow?