…Whether it's ChatGPT, Claude, Gemini, or something else, my work and personal needs are met without logging into an LLM throughout the day. Sure, I might be consuming LLM-powered results…
…It's not been six months since orchestrators for Claude and other LLMs started taking over GitHub, but that's a long time in frontier model time, and the LLMs have gotten…
…It already felt powerful, but I still had to manually search, summarize, and connect ideas. That’s where the self-hosted LLM took things to the next level. Logseq An open-source…
…As powerful as local LLMs have gotten, however, they face a fundamental limitation : their knowledge is frozen at their time of training, so they’re prone to making things up. They’re…
…It puts guardrails and guidance into the LLM at every stage, and makes me feel like an engineering manager and not a lone coder. It's now an indispensable part of my…
…powerful hardware at all. The biggest update that the Gemma 4 models got is something called intelligence-per-parameter. This means getting smarter results out of fewer resources. Google has engineered these…
…And let me tell you, this powerhouse of an LLM can walk toe-to-toe with pricey cloud models for development workloads – all while running on my weak hardware. Getting Qwen3.6…
…The way an LLM works is that when you ask ChatGPT something, your prompt gets sent to a massive model sitting on powerful servers somewhere in a data center. Want to stay…
…Sign in to your XDA account I got into local LLMs because it seemed interesting, if I’m being completely honest. Running my own AI on my own hardware just felt like…
…That's powerful stuff, and a guardrail against me putting information into the LLM prompts that I might not understand before I ask for an explainer. Related The engineer behind NotebookLM's…