I do think it's obvious (sometimes painfully so) that ChatGPT and other LLMs/neural network based tools will be an increasingly important tool in the coder's toolbox. With the Dall-E 3 art plugin, they can also be used for a bit of fun. Here are three images of my long-term mascot "Alien Bill" - well, two out of three ain't bad... when the scene grew more complex I couldn't persuade the system to stop reverting to a more classic alien form... cute rocket ship though!
I had similar problems getting GPT-4 to construct a single page Leaflet webapp - the core was solid, but each iteration lead to regressions of earlier functionality, and data structures were munged rather than evolved.
This difficulty in prompt wrangling - where you run into the fact that LLMs are not REALLY modeling the world "in their head", but getting extraordinary results based on guesses about what seems likely to say (or paint) next - poses the $50,000 question: is this challenge fundamental to LLMs? Are we near the top leveling off of an "S-shaped" curve? (And/or is there any other form of general AI waiting in the wings?) Or do we just need to be better prompters - either by improving our own human skills, or by utilizing intermediate "prompt-helpers"?
PLUG: I am a Boston-area software developer (with a focus on UI and UX, but proven abilities across the stack) looking for a team. See my portfolio at https://kirk.is/portfolio/ and let me know if I might be a fit for your company's team!
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