Jet_Xu's comments

On: Ask HN: LeetCode, anyone still doing it?

[Jet_Xu]

It depends on whether nowadays FLAG will still need engineer write code during interview.

On: AI still can't figure out PowerPoint

[Jet_Xu]

You are right but it is not because the weakness of AI, it is because all AI generation app are built by those coder only know .md files. They do not know what a consultant level slides looks like.

See this demo in the middle I show some top level strategy business slides (they are all generated by AI) https://youtu.be/Sq3a5qxsLwM

I am also working on such tool :)

On: AI Can't Read an Investor Deck

[Jet_Xu]

Try DocMason it is born for agentic analyze messy office files.

https://github.com/JetXu-LLM/DocMason

Demo video: https://youtu.be/Sq3a5qxsLwM

On: Is RAG Dead? Long Context, Grep, and the End of the Mandatory Vector DB

[Jet_Xu]

If you want to get knowledge from KB within 10 seconds, then traditional RAG (embedding+vector based) is still the most efficient way -- maybe more in consumer facing search / chat area.

If you want to get most precise and useful information from KB in minutes, then Agentic RAG is the key.

On: LLM Wiki – example of an "idea file"

[Jet_Xu]

I believe Multimodal KB+Agentic RAG is a suitable solution for personal KB. Imagine you have tons of office docs and want to dig some complex topics within it. You could try https://github.com/JetXu-LLM/DocMason

Fully retrieve all diagram or charts info from ppt and excels, and then leverage Native AI agents(e.g. Codex) to conduct Agentic Rad

On: Show HN: DocMason – AI Agent Knowledge Base for local complex office files

[Jet_Xu]

I am so sorry that I post two duplicate post in Show HN for same project

please just refer to this post with main content in the body (pure hand write content no AI generation ^-^): https://news.ycombinator.com/item?id=47640770

And could anyone help or tell me how to delete this post?

[dang → Jet_Xu]

We'll delete it for you.

[subdomain → Jet_Xu]

You should just be able to press delete.

[Jet_Xu → subdomain]

I pressed Hide, but still not work. And I do not have a "delete" button under this post. It is really awkward...

On: Ask HN: Do you code remotely from your phone?

[Jet_Xu]

No, too harmful for my eyes...

On: Why is Hacker News such an oldschool page?

[Jet_Xu]

What I want is markdown format support in Hacker news. But other features really not important :)

On: DeepSeek v3 beats Claude sonnet 3.5 and way cheaper

[Jet_Xu]

Please refer to my recent AI Code review performance test include DeepSeek V3: https://news.ycombinator.com/item?id=42547196

On: What do you check first in PR review? Help shape our AI Code review tool

[Jet_Xu]

A few weeks ago, I shared LlamaPReview (an AI PR reviewer) here on HN and received great feedback [1]. Now I'm trying to understand how experienced developers prioritize different aspects of code review to make the tool more effective.

When you open a PR, what's the first thing you check? Is it:

- Overview & Architecture Changes - Detailed Technical Analysis - Critical Findings & Issues - Security Concerns - Testing Coverage - Documentation - Deployment Impact

I've set up a quick poll here: https://github.com/JetXu-LLM/LlamaPReview-site/discussions/9

Current results show an interesting split between "Detailed Technical Analysis" and "Critical Findings", but I'd love to hear HN's perspective:

1. What makes you trust/distrust a PR at first glance? 2. How do you balance between architectural concerns and implementation details? 3. What information do you wish was always prominently displayed?

Your insights will directly influence how we structure AI Code Review to match real developers' thought processes.

[1] Previous discussion: https://news.ycombinator.com/item?id=41996859