Sivaji Panda sivajipsb

LLM Wiki

A pattern for building personal knowledge bases using LLMs.

This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.

The core idea

Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.

Next.js client-only SPA example

Made this example to show how to use Next.js router for a 100% SPA (no JS server) app.

You use Next.js router like normally, but don't define getStaticProps and such. Instead you do client-only fetching with swr, react-query, or similar methods.

You can generate HTML fallback for the page if there's something meaningful to show before you "know" the params. (Remember, HTML is static, so it can't respond to dynamic query. But it can be different per route.)

Don't like Next? Here's how to do the same in Gatsby.

I'm soon going to join Amazon Dublin from India and got opportunities to interview with Meta London, Zalando Berlin, Klarna & some other companies. I extensively researched about companies hiring internationally which support visa & relocation for SDE1/2 and above. So sharing list of companies with all of you:

Do consider to UPVOTE, if it helped you.

London

I'm soon going to join Amazon Dublin from India and got opportunities to interview with Meta London, Zalando Berlin, Klarna & some other companies. I extensively researched about companies hiring internationally which support visa & relocation for SDE1/2 and above. So sharing list of companies with all of you:

Do consider to UPVOTE, if it helped you.

London

I've recently joined Amazon Dublin from India and got opportunities to interview with Meta London, Zalando Berlin & some other companies. I extensively researched about companies hiring internationally which support visa & relocation for Tech roles. So sharing list of companies:

Do consider to STAR, if it helped you.

London

GROKKING NOTES

I liked the way Grokking the coding interview organized problems into learnable patterns. However, the course is expensive and the majority of the time the problems are copy-pasted from leetcode. As the explanations on leetcode are usually just as good, the course really boils down to being a glorified curated list of leetcode problems.

So below I made a list of leetcode problems that are as close to grokking problems as possible.

Pattern: Sliding Window

ANNOUNCEMENT

I have moved this over to the Tech Interview Cheat Sheet Repo and has been expanded and even has code challenges you can run and practice against!

\

	"""
	The most atomic way to train and run inference for a GPT in pure, dependency-free Python.
	This file is the complete algorithm.
	Everything else is just efficiency.

	@karpathy
	"""

	import os # os.path.exists
	import math # math.log, math.exp