Data Science

A curated guide to 10 AI newsletters organized by purpose: daily news, technical research, policy analysis, and builder ecosystem coverage.

This week's top picks cover LLM optimization, SQL portfolios, Git worktrees, agentic AI, and Python patterns for production-ready data workflows.

Five free resources covering agentic AI from hands-on courses to foundational theory. Build, understand, and evaluate agents that actually work.

Build a local video summarization pipeline using SmolVLM2-2.2B. Runs on consumer GPUs with 5.2 GB VRAM, no cloud API required.

LAMs and agentic LLMs both take actions, but differ fundamentally in how. Learn which to use and when.

GraphRAG and Vector RAG serve different retrieval needs. This guide breaks down their architectures, query handling, and when to use each.

A reproducible benchmark shows classical ML owns the synchronous payment hot path, while LLM agents belong on the asynchronous cold path.

A large context window is not the same as agent memory. Learn how retrieval, compression, and summarization fit into an agent's cognitive stack.

Seven open-weight coding models worth running locally in 2026, from efficient MoE models to multimodal options, all tested on consumer GPU hardware.

AI tools now let anyone build agents without Python. But prompting frameworks and hardware specs still separate casual users from serious practitioners.

Learn how to give Claude Code browser access via Playwright MCP so your coding agent can test and verify its own implementations end-to-end.

When a PDF prints a table of contents but ships no outline, RAG pipelines lose document structure. This article shows how to reconstruct it programmatically.