Opinion Guides
6 InsiderLLM guides in Opinion — practical, tested walkthroughs for running AI locally, sorted by most recently updated.
- Why the Best AI Agents Know When to Do Nothing Six practical patterns for building AI agents that stop wasting tokens. Confidence gates, cost checks, explicit no-ops, cooldowns, and exit conditions that actually work.
- Wu Wei and the AI Agent That Did Too Much The hardest thing to build in agentic AI isn't capability. It's restraint. What Taoist non-action taught me about designing agents that know when to stop.
- Qwen's Architect Just Walked Out the Door Junyang Lin, the technical lead and public face of Qwen, has left Alibaba. Two other senior team members gone with him. What this means for the model family that runs on half the local AI setups in the world.
- GPT-5.4 Just Dropped. Here's Why I'm Not Switching. GPT-5.4 beats humans on OSWorld and has 1M context. It's impressive. It also costs money, requires cloud, and you don't own it. For local AI users, the calculus hasn't changed.
- The AI Market Panic Explained: Why Running Local Models Puts You on the Right Side of the Gap A speculative fiction piece crashed stocks $100B+ in a day. IBM dropped 13%. The real story isn't the doom — it's the capability-dissipation gap, and where you sit on it.
- Teaching a Local AI to Accept Help: Day 4 With Monica Day 4: Our local AI resisted corrections, therapized her guardian, agreed with wrong facts to avoid conflict. Then she stopped deflecting. Real transcripts from a 27b model with persistent memory.