The problem is that you are using it for a "deceptively difficult task" and not "a task I know how to do, or could easily look up, but would prefer not to". Loo

The problem is that you are using it for a "deceptively difficult task" and not "a task I know how to do, or could easily look up, but would prefer not to". Looking at my ChatGPT history, some things I've used it for in the last week (all GPT-4): * Formatting a huge confusing blob of python code, markdown, and json into something readable. * Writing "boring" python functions needed to interface with AWS DynamoDB & S3. * Going from 0 -> 1 on a side project creating printable QR codes that redirect to custom links with logging. (Literally gave me picture perfect step by step instructions here, as if it was reading off the AWS UI. The sole issue I had it helped me troubleshoot). * JS tutoring. * Integrating an unfamiliar authentication provider with a web app. It gave me boilerplate code that needed like 1-2 tweaks to work perfectly. * Long winded architectural discussion giving me ideas on where to take internal libraries. Other than that, I've actually found that the github copilot CLI is a fantastic tool I've been turning to more and more. There are so many CLI tools that I kinda sorta remember the flags for, and now I no longer have to munge about looking things up. Just earlier I needed some test api key and I just said "!! generate a random api key", and it immediately came back with "openssl rand -base64 32". That works, and saved me time googling it. Also, your prompt here is pretty weak. For something complex you need to be very specific and give it explicit instructions on how to reason through the problem, explain it's thinking, etc. I find the more context I provide in the prompt, the better it performs. In particular leveraging the system prompt makes a big difference.