09:44
Claude Code 2.0 Is Finally Here
Claude Code's native scheduled tasks feature — which allows any skill or workflow to run automatically on a cron schedule without man...
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12:28
Using AI and Math to Auto-Generate + Backtest UNBEATABLE Trading Strategies (Build Your Own)
This tutorial extends a series on building AI-powered algorithmic trading systems, focusing specifically on how to add Monte Carlo si...
27:43
Step-By-Step Using Claude Code to Auto-Generate & Backtest Trading Strategies (Secret Easy Method)
This step-by-step tutorial from the Trade Tactics channel shows how to use Anthropic's Claude Code CLI with Claude Opus to automatica...
14:00
I Coded an AI Waifu that Controls My PC (Claude Cowork + ThreeJS)
Alpha Stack walks through building 'Claudina,' a 3D animated desktop companion that integrates with Claude Code's MCP server to give...
28:30
Claude Opus 4.6 CONTROLS MY PC: Creating a Robust Trading Bot (Statistically Verified)
The Trade Tactics channel demonstrates using Claude Opus 4.6's computer use capability to autonomously build, backtest, and optimize...
09:14
MimiClaw: Run this OpenClaw Variant on a $5 Chip
Fahd Mirza covers MimiClaw, the most unconventional member of the OpenClaw AI assistant family: a complete AI agent — LLM calls, tool...
24:54
Kalshi Order Book Watcher: Websockets For Real-Time Data
Part Time Larry documents both the motivation and technical implementation of a real-time order book watcher for Kalshi, the US-regul...
15:14
Building a $10,000/mo Trading Engine: Claude 4.6 (+ Monte Carlo Simulations)
The Trade Tactics channel demonstrates how to use Claude Opus 4.6 as an autonomous overnight agent to build, test, and optimize an al...
08:18
OpenClaw vs PicoClaw vs NullClaw vs ZeroClaw vs NanoBot vs TinyClaw — The Comparison
Fahd Mirza delivers a structured comparison of seven tools in the rapidly expanding OpenClaw family: OpenClaw, ZeroClaw, PicoClaw, Ir...
09:28
KittenTTS: The 25MB AI Model That Speaks: Local CPU Setup Guide
KittenTTS v0.8 introduces a trio of ultra-lightweight text-to-speech models — nano (25MB, 14M parameters), micro (40M parameters), an...