I recently switched roles to a "data engineer" and had to pick up on many new tools I had no experience with (k8s, helm, Victoria Metrics, grafana, and a few others). In the past I would have spent probably 1+ year using these tools in inefficient or outright incorrect ways while I struggled to get a practitioner's understanding of how everything works.
Now I've developed a prompt that I think gives very good results for pair programming and iterative debugging. I discus almost everything I learn related to these tools with gpt4 to confirm my understanding is correct, and also use it for generating yaml or templating other programs.
In some ways I am a little weary of how much I use the tool since OpenAI can theoretically take it away at any time. I am heartened by the rapid development of other open models (phind code llama seems very interesting), but will continue to use GPT4 for now as its indisputably the best model out there.
Now I've developed a prompt that I think gives very good results for pair programming and iterative debugging. I discus almost everything I learn related to these tools with gpt4 to confirm my understanding is correct, and also use it for generating yaml or templating other programs.
In some ways I am a little weary of how much I use the tool since OpenAI can theoretically take it away at any time. I am heartened by the rapid development of other open models (phind code llama seems very interesting), but will continue to use GPT4 for now as its indisputably the best model out there.