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Tag: AI

AI, Development

Game theory logic: why raw data lies about strategy

Raw averages describe a world that was not reacting to you. This post uses the penalty kick problem to show why competitive data needs mixed strategies, and what that looks like in pricing, fraud detection and WordPress backends.

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Core Updates, Development

WordPress Playground goes permanent with my.WordPress.net

my.WordPress.net turns WordPress Playground into a workspace that survives a page reload. The site lives in browser storage instead of on a server, and Blueprints handle the setup. Clear your cache without a backup and it is gone.

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AI, Development

Why your AI search evaluation is probably wrong

Vibe-checking search results is how teams end up rebuilding a backend for a system that scores worse than the SQL it replaced. What a real AI search evaluation needs: a golden set, repeated trials, and an ICC check before you ship.

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AI, Development, E-commerce Development

Causal inference in data science, the skill AI can’t fake

AI infrastructure spending hit nearly $400 billion in 2025 against barely $100 billion of revenue. The skills that survive that correction are the classical ones: causal inference, experiment design, Bayesian reasoning, domain modeling and SPC.

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Core Updates, Development

WordPress 7.0 Beta 3 rewires the AI provider screen

WordPress 7.0 Beta 3 ships 148 fixes and swaps the static AI provider list for the WP AI Client registry. Here is what changed in the connectors screen and how to test it on staging before the April 9 release.

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AI, Development

Agent skills architecture: why Markdown is not enough

A tool is one capability, a skill is the orchestration around it. Notes on writing agent skills in Python instead of Markdown, and where MCP fits when you build agents outside Claude.

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AI in WordPress, Design, Development

Why human strategy still runs an AI-accelerated workflow

AI raised the floor on production, and that changed what designers are actually paid for. Here is where human strategy still decides the outcome, and why judgment now carries the accountability.

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AI, AI in WordPress, Development

Machine learning at scale: availability beats accuracy

Machine learning at scale is an infrastructure problem before it is a modeling one: why availability beats accuracy, how label leakage fakes good metrics, and why heavy models and fallbacks belong on different hardware.

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AI, Development

The host memory bottleneck that halved Gaudi on AWS

Intel’s Gaudi accelerators lost half their throughput on AWS DL1 because every byte detoured through host DRAM. This is how Peer Direct, libfabric and DMA-BUF put that data path back on the network.

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AI in WordPress, Development

How I get production-ready code out of Claude Code

Vibe coding a feature is easy; keeping it out of the technical debt pile is not. A CLAUDE.md handbook, plan mode before any edit, and a review pass that assumes something is broken.

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