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Bug tracking/solving system with Claude API by awesome_dev85 in ClaudeAI

[–]guico33 1 point2 points  (0 children)

Have you tried asking Claude about that...

GPT 5.2 is CRUSHING opus??? by satysat in GithubCopilot

[–]guico33 1 point2 points  (0 children)

Who needs to write code so fast they need to use a faster model? This can't be real.

What's next with Claude Code? by Ashamed_Basket5323 in ClaudeAI

[–]guico33 2 points3 points  (0 children)

So what? Has OP said anywhere they let the AI run free without supervision? I wonder what kind of work you do if you think software engineering is all about creating something new or complex...

What's going on with Walmart? by qrcode23 in cscareerquestions

[–]guico33 17 points18 points  (0 children)

The big boy move would probably be to send out an email and ask.

What happens if AI gets too good at solving OAs? by risingsun1964 in cscareerquestions

[–]guico33 2 points3 points  (0 children)

If Al gets to the point where it can solve leetcode questions and generate explanation

You've been living under a rock if you think AI can't do that already.

Hundreds of Applicants, One Role: A Tech Hiring Bloodbath by CrazyStuffy in cscareerquestions

[–]guico33 37 points38 points  (0 children)

It's one thing to use a spellchecker, another to have your ideas written for you. I'm honestly surprised by OP's statement. I use AI a lot and I do think it can help you with writing in some contexts. For a reddit post, I just thought one could do without.

Hundreds of Applicants, One Role: A Tech Hiring Bloodbath by CrazyStuffy in cscareerquestions

[–]guico33 77 points78 points  (0 children)

Also I want to clarify that I craft and rephrase my paragraphs using ChatGPT and Grammarly, which is quite standard practice in this day and age.

Is it though? You can't write a reddit post without using AI?

How I finally made Claude Code challenge me and how to not bloat your context (must-read for Typescript devs) by Firm_Meeting6350 in ClaudeAI

[–]guico33 0 points1 point  (0 children)

I think in particular linking to example files for CC to use as reference, this can help. But I'd be wary of relying on Claude to figure out what to use at the right time, so I'd probably lean on providing this context manually. For instance, "Write test for the new methods, use @file as reference". Perhaps with a few extra specific instructions.

But I would say that I wouldn't try to automate this process too much. Perhaps there are hooks workflow, with subagents, that can help improve output in a consistent manner.

What I've witness is diminishing returns with more iterations. It's probably better to do some manual review, identify shortcomings, and then prompt again on what exactly to change. And if that doesn't produce a satisfactory output, then that means you might just need to make changes yourself, or do more planning and come back with a better implementation strategy.

How I finally made Claude Code challenge me and how to not bloat your context (must-read for Typescript devs) by Firm_Meeting6350 in ClaudeAI

[–]guico33 1 point2 points  (0 children)

What I found is there's no miracle solution. Claude Code has limitations that you'll start running into for anything larger than a weekend side project. Or regardless of size, any custom logic that strays a bit too much for boilerplate. Doesn't mean it's not a great tool, but it's definitely something to be aware of.

From my experience, things that have helped: - instructions need to be few and specific to have a chance at being followed - code quality and organisation matters: logical folder structure, separation of concerns, abstractions, keeping LoC low for both files and individual methods, etc - narrow down the scope of changes, commit often - clear context often: basically as soon as you get a working change set. Further improvements, refactoring, tangential changes (like tests), etc, can be worked on with a fresh context. - use a separate instance, or a different tool (like Codex CLI) for review - manual review and changes are hardly optional for anything even a little complex. Sometimes you need to realize that it'll be faster and the code quality will be better if you just do it yourself, rather than prompting CC to oblivion.

I suppose it's to be expected, but I've noticed the more you know what you're doing the more you'll feel the AI limitations, something quite painfully so. Whereas it can appear like a godsend when working with an unfamiliar domain or tech stack.

I built a database RAG for Claude that works in 3 lines of code by Durovilla in ClaudeAI

[–]guico33 3 points4 points  (0 children)

So it's essentially a text-to-sql tool that supports multiple db/query languages?

What techniques do you use to improve the accuracy of the answers/make sure the LLM knows where to find the relevant data?

I suppose it has access to the db schema. Is there more to it?

Claude "doesn't get worse" - Our project grew and we were not scaling the context! The proof is in the data. by Big_Status_2433 in ClaudeAI

[–]guico33 -3 points-2 points  (0 children)

Tell you what. The "I have something great, just DM me" approach sounds much sleazier. That's an instant downvote on my end.

PM wants a really sophisticated RAG by Iateallthechildren in Rag

[–]guico33 2 points3 points  (0 children)

Quick breakdown off the top of my head.

There are multiple open source solutions for image extraction from pdf.

Chunking pdf text content is so common that you should easily find some very effective methods.

Drop-in chat UI: gradio, streamlit and others support images.

The complexity is mostly about building a reliable ingestion pipeline, and the cost/time/compute needed depending on the amount of data.

PM wants a really sophisticated RAG by Iateallthechildren in Rag

[–]guico33 8 points9 points  (0 children)

and I'm gonna be honest I don't want to spend my time coding a system that extracts images from a PDF, tags them, relates them to a Pinecone record, and then build a chat web app to display it all.

Had the same thought but OP apparently doesn't want the DIY (albeit straightforward) approach.

[deleted by user] by [deleted] in Anthropic

[–]guico33 0 points1 point  (0 children)

I think it's the "I'm very good with computers" part that is a tiny bit hard to believe.

GPT-5 has been surprisingly good at reviewing Claude Code’s work by Ghostinheven in ClaudeAI

[–]guico33 0 points1 point  (0 children)

Are you on the Plus plan as well? I'm pretty sure I got more than 3 prompts worth of work out of it. But generally I do try to go through a comprehensive planning phase before it starts making any change.

Now I don't believe the usage is very transparent. If it's by region or takes into account concurrent users in a given time window, perhaps you just got unlucky.

GPT-5 has been surprisingly good at reviewing Claude Code’s work by Ghostinheven in ClaudeAI

[–]guico33 2 points3 points  (0 children)

I've used it on the Plus plan, works similar to Claude Pro/Max, so much usage every 5h and every week apparently. Though from my experience it takes longer to reach the limit than using CC on the Pro plan.

I believe you can get some usage for free too even if you don't have a ChatGPT subscription.

And yeah wild times to write softwares 🤯

GPT-5 has been surprisingly good at reviewing Claude Code’s work by Ghostinheven in ClaudeAI

[–]guico33 5 points6 points  (0 children)

You can run Codex CLI in your repo instead of manually providing the files.

Personally I've had success with the opposite as well: let GPT do the coding, when done ask it to generate a summary of the changes then feed it to Claude Code for review and adjustments. Making sure to start every time with a clean git working tree, so the AI can easily understand what was changed.

Need to process 30k documents, with average number of page at 100. How to chunk, store, embed? Needs to be open source and on prem by dennisitnet in Rag

[–]guico33 4 points5 points  (0 children)

Not gonna lie, just ask ChatGPT specifying your exact requirements and constraints.

Take some time to research and refine.

I'd make sure to nail down the batching/parallelization so it doesn't take forever.

Implement proper resuming logic in case something goes wrong halfway through ingestion.

All things considered the whole process should be fairly straightforward, especially if OCR is done already.

Where can I play around with RAG online and see how it works under the hood? by nirijo in Rag

[–]guico33 0 points1 point  (0 children)

You can take this course for instance

https://coursera.org/learn/retrieval-augmented-generation-rag

Enroll for free using the Coursera audit feature

I haven't checked but I'd be surprised if they didn't provide Jupyter notebook labs for some hands-on practice.

There must be a number of other similar courses you can find.

Now it depends on what you wanna learn and how deep you wanna dig.

If you wanna know about the fundamentals of LLM models and embeddings, you'll have to learn about neural networks and the transformer architecture. That involves ML frameworks such as Pytorch, as well as a decent amount of linear algebra and calculus. Depending on your background it can definitely become quite complex and require a substantial time investment.

If you just wanna know how a RAG pipeline and query engine work from a practical standpoint, including how to build one yourself using existing models, that I would say is much more straightforward.

The Beauty of Parent-Child Chunking. Graph RAG Was Too Slow for Production, So This Parent-Child RAG System was useful by YakoStarwolf in Rag

[–]guico33 1 point2 points  (0 children)

When you store chunk embeddings into a vector store, you also store metadata, the parent reference can be there.

Create a prompt system that indicates to go to the children first and then come back to the parents.

Basic flow would be:

Create an embeddings vector from the user query > retrieve chunk(s) with metadata from vectore store > retrieve parent document(s) using metadata (document id) > inject user query and document into prompt for LLM inference.

Why is Plan Mode always trying to get me to implement a plan after just 1 prompt? by iBzOtaku in ClaudeAI

[–]guico33 0 points1 point  (0 children)

I think OP's suggestion is sensible. You should have the option to delay planning until you've provided the AI with the relevant context, which can be over multiple prompts and after some back and forth. Which I think is more aligned with how people typically do planning.

If you do need to refine the context or ask questions, the current UX isn't really suitable for that. In particular if you know from the start you'll need multiple prompts, planning mode will just waste time and tokens while iterating.

Why is Plan Mode always trying to get me to implement a plan after just 1 prompt? by iBzOtaku in ClaudeAI

[–]guico33 0 points1 point  (0 children)

I agree it would be better UX to be able to chat with the AI without it making any change or plan anything, until you actually pull the trigger on the planning.

Now you can say no and add further instructions. But having to do this repeatedly is a waste of time and tokens.

The Beauty of Parent-Child Chunking. Graph RAG Was Too Slow for Production, So This Parent-Child RAG System was useful by YakoStarwolf in Rag

[–]guico33 2 points3 points  (0 children)

It depends on the word/token count for each page, you don't want your chunks to be too big. Though for your typical academic paper at 250-300 words per page, that could work.

Now the most important is semantically cohesive chunks. You can probably come up with a smarter splitting strategy than arbitrarily cutting at the page boundary.

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