Readit NewsPlease link to your history when you get one of these things to build my example so I can see how you managed to do it.
First, a friend without technical knowledge wanted to query an API using SQL. (At a previous firm he learned how to write “SELECT * FROM … WHERE …” statements.)
He asked one of these llms to do this, that he paid a premium for, and it suggested installing VSCode and writing an extension to ingest an API and to query it with python.
I am unfamiliar with VSCode so I’m unsure if this is even feasible, but after 3 days of trying to get it to work, he asked me, and I set up a python environment for him, and wrote a 5 line script to allow him to query the data ingested from the API into SQLite.
For me, the last time I tried, I asked one to write me a container solution using Docker that allowed for live coding of a Clojure project. I wanted it to give me solutions for each: deps.edn and lein.
I wasted hours, because it always felt “just around the corner”, trying to get it to output anything of use for either paradigm then when I abandoned the llm I quickly found, via a web search, a blog post someone wrote that did exactly what I asked, for a lein project of their own, and I just changed it to work for my project, and then again for the deps.edn version on my own.
With that said, the space is moving incredibly fast and the latest Claude/GPT-o1 are far ahead of anything that was available 3-6 months ago. Unfortunately Claude doesn't allow sharing publicly like ChatGPT, but here is a gist of Claude's answer for +- the same question your friend asked:
https://gist.github.com/ldorigo/1a243218e00d75dd2baaf0634640...
I'm on mobile so it wasn't handy to quickly paste an example API request/documentation for the LLM to follow; so there's a chance it might have hallucinated some if the API parameters - but if I included that; in my experience the code would work on first shot 90% of the time.
Regarding your second query, I'm too unfamiliar with clojure and the two solutions you mentioned to really understand what you were trying to achieve, but if you explain just a little bit more, I'm happy to record a screencast of me figuring it out with llms/genai tools from the ground up. What do you mean with "a container solution that allows for live coding"?
I am a developer with >25 of professional experience.
I am unable to get these things to do anything useful.
I’ve tried: different models, limiting my scope, breaking it down to small tasks, prompt “engineering”; and am still getting less than useless results.
I say less than useless, because I will then additionally waste time debugging or slamming my head against the wall the llm built before I abandon it and go to the official docs and find out the llm is suggesting an API access paradigm that became deprecated in the last major version update.
People on this site love to talk about “muh productivity!”, but always stop short of saying what they got from this productivity boost: pay raise, less time working; or what they built, what level of employment they are, or who they work for.
Are all of these posts just astroturfed?! I ask that sincerely.
Do you all just make “todo SPAs” at your employers?
Given the right context and the right choice of model/tools, I think ~90-95% of the code I write could be generated. And this is not for doing trivial CRUD; I work on a production app with 8 other people.
I'm really curious if you could give examples of problems that you tried and failed to use these tools for?
This time it was, "Did Paul Edwin Zimmer write a fourth Dark Border novel?" (Real answer: Yes, Ingulf the Mad. You can find the answer on his Wikipedia page.[1])
ChatGPT's[2] answer: "Yes, Paul Edwin Zimmer wrote a fourth novel in the Dark Border series titled "The Dark Border." This book was published after the original trilogy, which included "The Dark Border," "The Gilded Age," and "The Silver Sphere." If you're interested in the themes or plot, let me know!" (Note: these are not the titles of the 2nd and 3rd novels in the series. Also, it gave me the same name for the putative 1st and 4th books.)
Pure hallucination.
1. https://en.wikipedia.org/wiki/Paul_Edwin_Zimmer 2. https://chatgpt.com/
We build an LLM-based conversational assistant deeply integrated in the Edtech ecosystem. We aim to relieve teachers and admin workers of tedious "easy" questions so they can focus on what's important. Moving towards knowledge management and course support.
Early startup, small, tightly knit team (5 engineers, 2 implementation/process-focused folks, 1 sales guy, 1 marketing gal, 1 chill product-centered CEO). We're slowly scaling and expanding.
Stack (not crucial but you should at least be proficient in python):
- FastAPI python backend - MongoDB - Langsmith (llm evals/observability) - - Next.js (react) frontend - AWS
We're a startup. We need a generalist/"get things done" mentality, and sufficient drive/curiosity to figure things out (and build them/fix them) on your own - we don't micromanage.
About the position: you'd start off supporting me with developing the AI aspects of the product - for now, mainly the conversational interface. This isn't a purely ML position; for now lots of the work is SWE/back-end dev. Projects on the roadmap: building robust testing and observability for LLM performance, experimenting with and improving the RAG pipeline, fine-tuning/distillation where relevant to reduce latency/costs, working on a voice interface.
Experience requirements: ~masters level education in relevant field (doesn't have to be a masters/formal education, but you need to convince us you have an equivalent level of experience/understanding) & 1y of full-time relevant work experience (can be as student job)
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Send e-mail at `luca @ learnwise . ai` with brief intro + CV :)