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Running Ollama on Constrained Hardware

Context

I’ve been curious about running local LLMs for development tasks — code review, summarisation, drafting — without relying on cloud APIs. Ollama makes this straightforward to set up, but most benchmarks assume beefy hardware. I wanted to know: what’s the experience like on a standard development machine?

My setup: a laptop with a 12th-gen Intel i7, 16GB RAM, integrated graphics. No discrete GPU. This is the kind of machine most developers actually use.

Testing AI Crawlability on a Static Hugo Site

Context

I wanted to understand how AI-powered search tools — things like ChatGPT browsing, Perplexity, and Google’s AI Overviews — actually crawl and interpret a static site. Most SEO advice is still written for traditional search engines. Does structured data actually help AI crawlers, or are they just parsing the raw HTML?

The question: if I add JSON-LD schema markup to a simple Hugo site, does it measurably change how AI tools understand and reference the content?

Optimising Websites for AI Discovery

Introduction

The way people find information is changing. Traditional search engines still matter, but AI-powered tools — ChatGPT browsing, Perplexity, Google AI Overviews, Claude’s web access — are becoming a significant discovery channel. If your content is well-structured and easy for these systems to parse, you’re more likely to be cited, referenced, and surfaced.