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Today at work I hadnt used apache spark in a long time. I needed to do some quick and dirty data analytics on large datasets. Rather than read documentation, I just put the queries i needed in english into chatGPT, and it spit out perfectly working code. The queries werent that complex, but it saved me hours googling a bunch of random spark SQL syntax. The old school way is google sends you links, and through those code examples, you build up all the edge cases you need for your code to work. Thats completely obsolete as a way to synthesize information! Google is going down! Thanks for reading my daily chat gpt anecdote! Sorry if its irrelevant, I just cant believe how much better it made my day. |
The perfect use case for ChatGPT for my personal workflow has been to give me the 70-percent-of-the-way-there skeleton for a given query, Terraform module, or even just to prevent myself from lookup up the syntax of for loops in <language> for the 30,000th time. I can then take that 70 percent chunk and bolt on my edge cases as I go.
There hasn't really been a time where the answer didn't need some massaging and of course occasionally it's flat out wrong, but that's becoming more and more apparent to me those instances are the result of feeding it sub-optimal prompts. I've found it to be eerily similar to my experience learning to use search engines back before SEO titles were a "thing."
It's frankly incredible how little I find myself using a traditional search engine compared to six months ago, at least in the context of work stuff. I'm less inclined to feed it general knowledge prompts, but it's encouraging to see the remarkable LLM tech leaps from generation to generation, and in such short order.