…I would primarily prompt it for quick bursts of information or a bit of brainstorming. But the problem showed up when I started throwing longer prompts at it. Its context limits as…
…the best of Anthropic’s agentic engineering and applies it to the things that actually slow us down — local file handling, data synthesis, and deep research organization. It’s practical, local-first…
…Every weird result gave me a reason to refine the prompts, adjust the feeds, or rethink a section label. That’s part of what makes the local approach satisfying. I’m not…
…running a local LLM would bolt Context7 on to improve the output. It's a well-documented MCP server that lets models look up real, current documentation for practically any library you…
…that setup is still expensive and not practical for most people. What I eventually realized is that the best way to use a local LLM is not to expect it to handle…
…doubles as the voice satellite Starting with the workflow I rely on practically every day, I’ve got a local voice assistant that initiates audio processing once it hears a wake word…
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