All I hear is anecdotal statements from people claiming LLMs have made them some percent more productive. Yet few actually say how or demonstrate it.
For the last year, I've tried all sorts of models both as hosted services and running locally with llama.cpp or ollama. I've used both the continue.dev vscode extension and cursor more recently.
The results have been frustrating at best. The user interface of the tools is just awful. The output of any models from Deepseek to quen to Claude to whatever other model is mediocre to useless. I literally highlight some code that includes comments about what I need and I even include long explicit descriptions etc in the prompts and it's just unrelated garbage out every time.
The most useful thing has just been ChatGPT when there's something I need to learn about. Rubber ducking basically. It's alright at very simple coding questions or asking about obscure database questions I might have, but beyond that it's useless. Gotta keep the context window short, or it starts going off the rails every single time.
For the last year, I've tried all sorts of models both as hosted services and running locally with llama.cpp or ollama. I've used both the continue.dev vscode extension and cursor more recently.
The results have been frustrating at best. The user interface of the tools is just awful. The output of any models from Deepseek to quen to Claude to whatever other model is mediocre to useless. I literally highlight some code that includes comments about what I need and I even include long explicit descriptions etc in the prompts and it's just unrelated garbage out every time.
The most useful thing has just been ChatGPT when there's something I need to learn about. Rubber ducking basically. It's alright at very simple coding questions or asking about obscure database questions I might have, but beyond that it's useless. Gotta keep the context window short, or it starts going off the rails every single time.