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Building AI Agents

Sayantan Das sayantan-manulife

Building AI Agents
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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.

@sshh12
sshh12 / slack-system-design-reverse-engineered.md
Last active April 4, 2026 05:29
A reverse-engineered system design of Slack's web application, built from live network traffic analysis of the authenticated Enterprise Grid experience. 200+ API calls captured across boot, search, messaging, reactions, and navigation. Every backend service named.

Slack System Design: A Grounded Teardown

A reverse-engineered system design of Slack's web application, built from live network traffic analysis of the authenticated Enterprise Grid experience. 200+ API calls captured across boot, search, messaging, reactions, and navigation. Every backend service named.

Architecture Overview

┌─────────────────────────────────────────────────────────────────────────────┐
│  BROWSER (Gantry v2 SPA)                                                    │
│                                                                             │
@sshh12
sshh12 / netflix-system-design-reverse-engineered.md
Created March 1, 2026 00:41
Netflix's web architecture reverse-engineered from live network traffic -- 18 named internal systems (Akira, Cadmium, Shakti, Pinot, MSL, FTL, Ichnaea...), dual API migration (Falcor → GraphQL), video streaming pipeline, DRM flow, search capability negotiation, and the full content data model. All from 177 captured requests.

Netflix System Design: A Grounded Teardown

A reverse-engineered system design of Netflix's web application, built entirely from live network traffic analysis of the authenticated browse experience. 177 requests captured, every API contract inspected, every subsystem named.

Architecture Overview

┌─────────────────────────────────────────────────────────────────────────────┐
│  BROWSER (Akira SPA)                                                        │
│                                                                             │
@intellectronica
intellectronica / 0.README.md
Last active December 21, 2025 09:56
GitHub Copilot CLI SKILL - use a variety of models (Gemini, GPT / Codex) from within Claude

GitHub Copilot CLI SKILL

Use models like Gemini 3 Pro, GPT-5.1, and GPT-5.1-Codex from within Claude by invoking GitHub Coplit CLI.

Installation

  1. Create ~/.claude/skills/github-copilot
  2. Save SKILL.md to ~/.claude/skills/github-copilot/SKILL.md
@markuskreitzer
markuskreitzer / README.md
Created July 16, 2025 18:20
How to get OpenAI Codex working with Azure

Configuring OpenAI Codex CLI with Azure OpenAI: A Working Solution

If you've been trying to get OpenAI's Codex CLI working with Azure OpenAI Service, you're not alone in facing configuration headaches. The ongoing transition at Azure, combined with inconsistent documentation and API version differences, can make this setup feel like navigating a maze blindfolded.

After countless hours of debugging 404 errors, stream failures, and authentication issues, here's a working configuration that actually works with Azure AI Foundry and GPT-4o.

The Challenge

The Codex CLI documentation provides a basic Azure configuration example, but the reality is more complex:

@artemgetmann
artemgetmann / claude-code-token-saving-guide.md
Last active May 5, 2026 12:27
Practical workflow for reducing token usage in Claude Code while preserving session continuity. Includes compacting strategies, CLAUDE.md structure, modular context management, and prompt engineering tips.

🧠 How to Save Context Tokens When Using Claude Code

This is a personal reference workflow for minimizing token usage while maintaining project continuity across Claude Code (Sonnet 4 with file access).


✅ Setup: Populate CLAUDE.md

Claude loads CLAUDE.md automatically at session start.

@jarnheimer
jarnheimer / export-pull-request.md
Last active August 29, 2025 08:05
Guide on how to export a pull request to a file

Export pull request

GitHub

Save a pull request as a pr.diff

curl -H "Accept: application/vnd.github.v3.diff" -u [username]:[personal_access_token] https://api.github.com/repos/[organization]/[repo]/pulls/[pull id] > pr.diff 

Replace

  • username your Github username