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Category: AI

AI, Development

Why range beats depth: the case for the data generalist

Hiring for hyper-depth became the default advice for WordPress teams, and it makes messy stacks harder to fix. My case for range, what generalists catch that specialists walk past, and how much of the specialist layer AI already covers.

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AI, Bug Fixing, Core Updates, Development

Why the MCP client is leaving Composer behind

Notes from the latest WordPress AI contributor meeting: the MCP client is becoming a normal plugin instead of a Composer package, the Abilities API is getting real exception handling, and AI agents are getting a proper block dictionary.

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AI, Bug Fixing, Development

Why ReAct agent retries waste 90% of your budget

In a 200-task benchmark, nearly 91% of ReAct agent retries were spent on errors that could never succeed. The three fixes I use: an error taxonomy, per-tool circuit breakers, and tool routing that stays in code.

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AI, Development

Survival analysis in Python for customer churn and LTV

Churn is not a yes or no question, it is a question of when. This covers censored data, Kaplan-Meier curves, and Cox hazard ratios in Python with the lifelines library.

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AI, AI in WordPress, Development

Claude Code for non-technical tasks, from slides to CRM

Claude Code is not only for refactoring PHP. Three things I run through it that never touch a codebase: LaTeX decks kept in Git, cross-app search over Slack and Notion, and prospect research.

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AI, Bug Fixing

WooCommerce bug fixing: the support team cleared 150 bugs

Woo ran a Bug Blitz: support engineers with Claude Code and Copilot shipped over 170 fixes across 20 products, every line reviewed by quality engineers. Why it worked and what to copy.

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AI, AI in WordPress, Development

How to give your AI coding assistant a memory

LLMs forget your stack the moment you close the tab. Here is what actually sticks: a project rules file in the repo, global rules for your own preferences, and MCP when the assistant needs data from outside the codebase.

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AI, Development

Why your GPU sits idle while the CPU pins at 100%

A GPU at 10% while every CPU core is pinned at 100% is a data loading problem, not a hardware problem. What I change first in a PyTorch pipeline: DataLoader workers, pin_memory, mixed precision and torch.compile.

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AI, Development

Voxtral voice cloning with the encoder weights missing

Mistral released Voxtral-4B-TTS with the encoder truncated, so there is no way to feed it a new voice. The way around it is gradient descent plus a straight-through estimator, optimizing the audio codes directly against an 8-second clip.

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AI, Development

Compiling programs into transformers instead of training them

Sean Moran’s work wires transformer weights analytically instead of training them: the residual stream becomes working memory and attention becomes a lookup. What that means when you need an exact computation instead of a probable answer.

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