Standard AI gives you a paragraph. Deep Research gives you a structured multi-source report with cited evidence — automatically. Learn the DEEP framework and 7 proven prompt templates that separate generic AI responses from professional research outputs.
We built a prompt compressor using only BERT attention scores — no extra LLM calls, no black box, 50%+ token savings on real prompts. Here's how it works, the complete code, honest benchmarks, and when to use it over LLMLingua-2.
I built an AI agent that detects my location, checks the weather, finds national parks, and gives me opinionated hiking recommendations — all running locally with zero cloud APIs. This is the 4-step agentic loop that powers every modern AI agent, and how to build one from scratch.
Learn to build a fully autonomous AI research agent using the Anthropic Messages API with web search via Tavily, PDF downloading, multi-turn memory, and a Streamlit UI. Step-by-step from zero to production.
Three hands-on interpretability techniques for understanding what language models think: attention visualization with circuitsvis, sparse autoencoders for hidden concept discovery, and steering vectors for behavior control—all with runnable code.
A developer would cost $10,000 and take 2 weeks. I built the same production-ready branded infographics tool in 2 hours for $0 using vibe coding — PRD first, then Google AI Studio, screenshots, and one-click deploy.