111–120 of 367 posts
I would like to give them a try but I certainly not have the money to get a system able to run them, and I don't really want to pay more than the state of the art
I seriously dont' know all this big hullabaloo about one shot prompting. by definition, a single prompt wont' constitute the complexity of a software project. ergo, what you'll get is a series of assumptions made by the model based on preexisting code in its training corpus. I'd rather see a coding agent that can follow steps in a plan file to a T while following guardrails and adhering to the proper coding conventio…
Earlier quoted context omitted.
> I'd rather see a coding agent that can follow steps in a plan file to a T while following guardrails and adhering to the proper coding conventions in the human reviewed spec. Guardrails/conventions should be enforced in linters, formatters, static analysis tooling; not specs/prompts.
It's not always possible, or at least trivial. For example how do you enforce "prefer to reuse existing code over making a copy"? Is there a static analysis tool that will detect two pieces of code that do the same thing?
I seriously dont' know all this big hullabaloo about one shot prompting. by definition, a single prompt wont' constitute the complexity of a software project. ergo, what you'll get is a series of assumptions made by the model based on preexisting code in its training corpus. I'd rather see a coding agent that can follow steps in a plan file to a T while following guardrails and adhering to the proper coding conventio…
Of course, with a software engineer at the helm - the models are going to be able to be guided to produce much better output. (Or worse, depending on the engineer!)
GLM 5.2 has one big issue that will limit its meaningful success and that's the value of their coding subscription. Yes, in terms of API pricing, GLM 5.2 outperforms the competition. But the only people that use API billing for their coding work are large corporations, where these highly subsidized subscriptions are being fazed out. At the same time, none of these companies will use a Chinese API for their employees.…
My impression is that individual subscriptions are the loss leading hook. The money is made on Enterprise token contracts. Employees and students used to coding with thousands of dollars worth of tokens (on a 20/100 dollar plan) will push enterprise to spend. Having a Chinese model that is competitive won't displace this enterprise spend. But an open model hosted in the US/EU might. The existence of GLM 5.2 puts a ce…
I just think that as of today, most people will not find a good reason to switch to GLM.
I seriously dont' know all this big hullabaloo about one shot prompting. by definition, a single prompt wont' constitute the complexity of a software project. ergo, what you'll get is a series of assumptions made by the model based on preexisting code in its training corpus. I'd rather see a coding agent that can follow steps in a plan file to a T while following guardrails and adhering to the proper coding conventio…
If a model can take a series of increasingly complex instructions and satisfy the requirements without human intervention, we can pretty easily decide how well overall the model does. And, judging better models just means adding more requirements to a task. So, I think it's a useful method (Even if it's not a realistic use case). Of course, with a software engineer at the helm - the models are going to be able to be…
To really evaluate how a model is to use in real life, it should have access to tools, and be able to iterate on something, like they do when you use them in an agent harness.
None of that iteration need necessarily to have a human driving it (although if you're building something you want to be able to maintain, you probably need a human driving the design and architecture), you can just let the model do a couple of tries and give it input into how it's doing, and you get something closer to how people use these models in reality.
GLM 5.2 has one big issue that will limit its meaningful success and that's the value of their coding subscription. Yes, in terms of API pricing, GLM 5.2 outperforms the competition. But the only people that use API billing for their coding work are large corporations, where these highly subsidized subscriptions are being fazed out. At the same time, none of these companies will use a Chinese API for their employees.…
My impression is that individual subscriptions are the loss leading hook. The money is made on Enterprise token contracts. Employees and students used to coding with thousands of dollars worth of tokens (on a 20/100 dollar plan) will push enterprise to spend. Having a Chinese model that is competitive won't displace this enterprise spend. But an open model hosted in the US/EU might. The existence of GLM 5.2 puts a ce…
Except there is no evidence of this at all, just people comparing API and subscription pricing. The leaked financial info for OpenAI shows inference is profitable right now, though it does not show a distinction between subscription and API revenue... but if subscription revenue was so lossy, it would hard for total inference to still be profitable.
I swear, if I read forms with “genuinely” one more time I am gonna scream. FUCK LLM WRITING