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ai deep-dive

Choosing an Agent Framework in 2026: LangGraph, CrewAI, MAF, AG2, Mastra, Pydantic AI, and DSPy

These seven tools are not one product category: LangGraph, MAF, and Mastra emphasize durable workflows; CrewAI and AG2 emphasize multi-agent collaboration; Pydantic AI emphasizes typed Python agents; DSPy optimizes AI programs against data and metrics. Choose the control model first.

ai deep-dive

DSPy: Compiling AI Programs with Signatures, Metrics, and Optimizers

DSPy replaces handwritten prompt strings with task Signatures, execution Modules, and Optimizers that compile better instructions and examples against a dataset and metric.

Stanford CS224U: The Course Site Stopped in Spring 2023, but You Can Clone the Whole Thing

CS224U's teaching material isn't a slide deck — it's an Apache-2.0 GitHub repo holding the lecture notebooks, all three assignments, and the grading document for the final project. But the on-campus course has skipped three straight academic years since Spring 2023, and ExploreCourses has it back on the books for Spring 2026-27. The official description still lists relation extraction and semantic parsing; the 2023 syllabus covers neither. And the data-loading cell in the first assignment breaks in a fresh environment today, on a Hugging Face compatibility change.

Stanford CS329Z: Hand-Build the Agent with litellm First, Then Let DSPy Take It Away

CS329Z is a new three-unit agent engineering course debuting at Stanford in Autumn 2026. Its first homework asks you to build RAG, tool calling and a ReAct loop from scratch with litellm, then rewrite the same components in DSPy and hand in the comparison. The course site lives in a public GitHub repo, and the commit log shows the assignment count dropping from three to two in mid-August — the one that got cut was 'Data for Agents'.