Ask HN: Feedback on my solo, local-LLM-only AI content pipeline (100 posts in)

A developer is building a solo, local-LLM-only AI content pipeline that produces human-reviewed articles on AI, hardware, and gaming, having published 100 posts. The project aims to avoid off-topic garbage by using local models and manual curation, contrasting with typical AI content tools that generate mediocre text.

Fetching posts Fetching posts Deep dives into AI, hardware, and the edges where they meet. Locally-published, human-reviewed, free to read. Compiler theory doesn't have a "move fast and break things" phase. The fundamentals -- lexing, parsing, semantic analysis, code generation -- have been settled for decades. We didn't set out to write about echo chambers. We set out to fix two content tasks that were producing off-topic garbage. What we found… For most of Poindexter's life, we didn't really have a UI. We had a stack of adjacent tools: Grafana dashboards for metrics, a Discord bot… For years, content strategy meant the same ritual: open a keyword tool, sort by volume, write toward whatever the tool told you people were… AI copilots produce things fast. Dashboards get built in minutes. Pull requests merge cleanly. Everything looks done. That speed is the… If you've been running models locally, you already know the drill. Every token an LLM produces requires a full forward pass through every… Most AI content tools follow a predictable pattern: they take a prompt, generate a wall of mediocre text, and call it "automation." For… Explore our complete collection of insights and analyses across AI, hardware, and gaming.