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AI, AI in WordPress, Core Updates

WordPress AI Client: what changed on the road to 7.0

The WordPress AI Client is being lined up for a core inclusion proposal. January 2026 contributor notes cover streaming leaving the PHP client, a kill switch filter for locked-down sites, and MCP for tool discovery.

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AI in WordPress, Development

WordPress AI Experiments 0.2.0: what actually changed

WordPress AI Experiments 0.2.0 adds AI-generated excerpts in the block editor and an Abilities Explorer screen under Tools. Here is what the release changes for plugin developers, plus the code for registering your own ability.

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AI, Development

Causal ML: why prediction alone breaks business decisions

Prediction models find patterns; they do not tell you what an action will cause. This post walks through the causal toolkit for that: potential outcomes, DAGs, de-biasing with OLS, propensity matching, and difference-in-differences.

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AI, Development

How Cursor codebase indexing actually works

Cursor’s indexer is a RAG pipeline: tree-sitter splits code at logical boundaries, embeddings land in Turbopuffer, and Merkle trees keep the index in sync. Here is how the pieces fit together, and what actually leaves your machine.

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AI, AI in WordPress, Development

You probably don’t need a RAG vector database yet

For a docs bot or an internal MVP, a dedicated vector database is more infrastructure than the problem needs. Vector search is matrix multiplication, and NumPy handles it in milliseconds. Includes a small store class, the SciKit-Learn upgrade path, and the four signs you have outgrown both.

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AI, AI in WordPress, Development

WP-Bench puts AI models through a real WordPress runtime

WP-Bench is the official WordPress AI benchmark. It runs model-written code inside a real WordPress runtime instead of asking a human whether the code looks right. How to run it, and what it still gets wrong.

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AI, Development

Getting a data science job in 2026 without 400 rejections

Most data science applicants in 2026 are studying the wrong things and applying everywhere at once. Notes from reading hundreds of resumes: what to learn first, how to aim applications, and why referrals do the work.

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AI, Development

Why specialist vision models still beat SAM3 in production

SAM3 has not made custom-trained detectors pointless. Benchmarks on wheat, CCTV and blood cells show specialist models like YOLOv11 running 30x faster and scoring higher, which is why foundation models belong in development.

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AI, Development, E-commerce Development

Azure ML vs. AWS SageMaker: how the infrastructure differs

A side-by-side look at Azure ML and AWS SageMaker: Workspace-centric RBAC against job-level IAM roles, Datastores against raw S3 URIs, and which one holds up once training moves off notebooks.

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AI, Bug Fixing, Development

A self-healing data pipeline for broken vendor CSVs

A vendor changed a CSV delimiter at 2 AM and my nightly import died. Here is the try, heal, retry loop I built with Pandas, Pydantic and Tenacity so the pipeline handles that class of error itself.

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