14:00
Building a Agentic AI Trading Heartbeat That Works
This video from the All About AI channel walks through a working agentic trading system built around a 'heartbeat' architecture: a li...
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25:53
Ghost AI let’s AI Agents build disposable worlds
Wes Roth introduces Ghost AI (ghost.build), a tool that creates isolated, disposable PostgreSQL database copies on demand—solving one...
09:39
Step 3.7 Flash – 198B Open Source Model That Does Everything; Does it Really?
Step 3.7 Flash is a 198 billion parameter sparse mixture-of-experts model from Step One, activating only 11 billion parameters per to...
08:53
LFM2.5-8B-A1B: Local Agentic AI with Multilingual Support Tested
LFM2.5-8B-A1B is Liquid AI's latest open-weight model — an 8.3 billion parameter mixture-of-experts architecture that activates only...
08:38
My AI Coding Workflow — Everything I Use Now (for peak performance)
Edmund Yong walks through the development of new features for CreateSkills, a browser extension and custom MCP server he's building t...
12:19
I Stopped Using PowerPoint After Building This Claude Code Skill (Full Tutorial + 3 Templates)
Product builder Peter Yang walks through how he replaced PowerPoint and Google Slides entirely by building a custom /slides skill ins...
12:42
I Automated My Entire Twitter Strategy With This AI Agent
Craig Hewitt walks through building a fully autonomous Twitter content agent using Twin, an AI agent platform with built-in browser a...
10:06
DFlash Leaves Qwen Territory – Gemma 4 31B Now Runs 5x Faster with Speculative Decoding
Fahd Mirza demonstrates the first end-to-end deployment of Llama Box DFlash with Google's Gemma 4 31B model, following the merge of P...
14:33
Running Local AI on AMD
Sam Witteveen takes a hands-on look at running local AI on an AMD workstation equipped with a Ryzen Threadripper 9980X processor and...
12:12
Microsoft Lens: Impressive on Paper, But Does It Deliver Locally? Let’s Test
Fahd Mirza installs and tests Microsoft Lens, a new 3.8-billion-parameter text-to-image model quietly pushed to Hugging Face, running...
01:18:46
The Only Polymarket AI Trading Bot Guide You Need in 2026
Prediction market trading on Polymarket requires more than intuition — it demands systematic research, liquidity awareness, and disci...
08:45
Agent Battle: Mine the most diamonds in 45 minutes
In this live workshop hosted by Anthropic's Applied AI team, engineers Ben and Jeff guide participants through building and deploying...
14:19
Why Creating a Fake SaaS Using AI Is So Profitable
This video from All About AI documents an experiment: how quickly can AI tools build a convincing fake SaaS product, and does the vir...
18:02
Fast Models Need Slow Developers — Sarah Chieng, Cerebras
Sarah Chang, Head of Developer Experience at Cerebras, argues that the arrival of ultra-fast AI coding models demands a fundamental r...
28:10
Anthropic Just Dropped a Masterclass on Building Agent Harnesses (for Large Codebases)
Cole Medin breaks down Anthropic's recently published guide on using Claude Code in large codebases, going well beyond a summary by b...
18:25
Your Coding Agent Should Do AI System Engineering — Ben Burtenshaw, Hugging Face
Ben Burtenshaw, an engineer at Hugging Face, makes the case that coding agents have crossed a capability threshold where they can now...