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What stack are they using? I am thinking it's pretty much any LLM (GPT-3/GPT-4), Lang chain with GPT Index.
I am guessing they build boilerplate templates and filling in functions with GPT outputs then using them to write unit tests for base cases?
I am guessing the truth is really closer to the centre.
For example (ChatGPT):
- Prompt:
Create a HTML select list with the following text values: "First In, Last Out", "Last In, First Out", "Random Order", "Round-Robin" give each option and the select list appropriate names and IDs.
First In, Last Out
Last In, First Out
Random Order
Round-Robin
Also, Copilot sometimes just does nothing, but there have been many instances now where it literally does exactly what I wanted. It's pretty random.
> What stack are they using? I am thinking it's pretty much any LLM (GPT-3/GPT-4), Lang chain with GPT Index.
I'm skeptical of any 'stack' that isn't just ChatGPT + GPT-4. It's probably whatever their flash in the pan startup is building right now. To me this seems like a horrible time to build up such a stack (personal or otherwise) rather than just getting proficient at ChatGPT and the plain old OpenAI API while waiting for new stuff like plugins to come out.
Personally I just have a go-to tech stack for GPT-based projects, composed of python, poetry, datasette, and click CLI's written by GPT-4 that can call out to OpenAI in order to manipulate databases (to then be viewed in datasette). But this is more for building little demos to try out GPT rather than incorporating into other work. Otherwise I just use ChatGPT alone. But TBH I'm far from 10x.
On a sidenote: You shouldn't take anything said in the "all in podcast" more seriously than a political discussion overheard a saturday night in a bar. Be careful with the halo effect.
What I would like to know is what is the best way to integrate an LLM and its output into my IDE without paying for something like Github Copilot. Any ideas here?
It gives me faster access to documentation/Stackoverflow, and creates bespoke templates. So I am "10x" but for the most tedious parts of "copy/paste" development. For the hard parts or the time spent thinking about design/flow, it does basically nothing. So am I "10x" overall? Absolutely not. I am barely even "2x" relative to before (since this is a minority of my time). For example (ChatGPT): - Prompt: Create a HTML…
me:
html select list of orderings: fifo, random, rr, lifo
GPT-4:
To create an HTML select list with different orderings, such as FIFO (First In, First Out), Random, RR (Round Robin), and LIFO (Last In, First Out), you can use the following HTML code:
Select List of Orderings
Choose an ordering method:
FIFO (First In, First Out)
Random
RR (Round Robin)
LIFO (Last In, First Out)
Submit
---
OK not exactly the same but just wanted to GPT-golf it. When lazymaxing for real, I just try to keep in mind that ChatGPT is already fine-tuned to include certain things, like following proper conventions, explaining its steps, commenting code. And that most of the time it'll make an educated guess rather than looking at me going "huh?" if it's unsure - so if there's really only 1 reasonable interpretation of terse instructions, I can drop the human-friendly cruft text.