AI Tutorials

Use Copilot Cowork to turn one sales CSV into an Excel workbook, Word briefing, PowerPoint deck, and Outlook draft, then check the results, save the workflow as a skill, and schedule it.

What if your AI coding agent could improve itself? We tested Google's Harness^2 with OpenCode and DeepSeek on JobBench to find out whether self-improving AI agents actually perform better.

Learn how to run powerful decision models locally, explore the vLLM ecosystem, and build three practical projects using text, images, and videos.

Build a GitHub CI repair workflow with DeepSeek Superagent, then use observe mode, pytest, holdout data, and human review to check one pandas fix.

Build a Python agent with Gemini 4 Argon, function calling, and profiling, then check its patches with hidden tests, benchmarks, and API cost.

Learn how Mercury 3 uses diffusion-based generation to build an incident analysis assistant, visualize refinement states, and compare low vs. high reasoning effort.

Use Meta Muse Wonder and Olostep web API to check medical claims, explain the reasoning, and show where the evidence came from.

Build a Python image-to-CAD agent with the Kimi K3.1 Pro API using vision input, tool calling, a Docker sandbox, a hidden evaluator, and cost tracking.

Learn what Gemini Embedding 2 is, how it compares to Nova, Voyage, and Qwen, and build a multimodal search app in Python with ChromaDB.

A hands-on Meta Muse setup guide for first-time users. Learn how to set permissions, connect tools, scope a task the agent can actually finish, and read the Activity log so you know what it did before you trust the output.

Decision models score a fixed set of answers instead of writing text. See how they work, how Jev compares, and what independent tests found.

A hands-on RAG evaluation tutorial in Python. Build an evaluation dataset, score it with the 4 core Ragas metrics, wire a quality gate into CI, generate synthetic test questions, and track scores across commits so you can tell a retrieval failure from a generation failure before your users do.