
Local AI / LLMs from Zero to Hero Article Series

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Don’t know where to start with Local AI? Read my Local LLMs From Zero to Hero series It covers:
– Hardware
– Software – Models Mechanics
– Everything else necessary Needs no prior experience Easy to understand for any background Local / Opensource AI FTW

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All covered in the last 5 articles I published Local LLMs from Zero to Hero
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clarifying: the issue is that alignment instructions and don’t pass, and the emotional weight that some people attach to LLMs can cause challenges that we would not see in a pure search engine.
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You should buy an RTX 3090 and learn how to run models locally The elite don’t want you to know this but running local models is hella easy, performant, and cheap nowadays
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Automation is a lie. CLIs are over. The SaaSpocalypse is dumb. A year ago @danshipper came on the podcast to predict where AI was heading. He was remarkably right—including the call that everyone was sleeping on Claude Code. Dan has a unique lens into where things are going

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Most people use Claude Code like a chat box. It's actually a 7-layer system. Each layer compounds on the one below it. The bottom layer (CLAUDE. md) is where 90% of users stop. The top layer (Subagents) is where the real leverage starts. Here's the full stack, from foundation
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What's Copilot Pro? I found this story from October saying Microsoft weren't selling that any more, having replaced it with "Microsoft 365 Premium" https://
microsoft.com/en-us/microsof
t-365/blog/2025/10/01/meet-microsoft-365-premium-your-ai-and-productivity-powerhouse/
… (I cannot make any sense at all of Microsoft's product naming around this stuff)
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It literally does not have any LLM like DeepSeek, which Japanese LLM ranks same or better than DeepSeek in benchmarks then?

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Turn any document into structured data for AI agents! Firecrawl just released a new parse endpoint. Upload local files or non-public documents and get back clean, LLM-ready data. The parse endpoint converts PDF, DOCX, XLSX, HTML, and other formats into Markdown, JSON, or