SMRTR summary
Self-hosted large language models (LLMs) offer privacy and customization benefits. Using open-source software like LM Studio or llama.cpp, users can run various models on personal devices. Model size and hardware impact performance, with 7-8B parameter models providing good results for most tasks.
SMRTR provides this summary for quick context. The original article belongs to Hacker News.
Read the original articleThis archive is built from SMRTR newsletter stories. Subscribe for hand-picked stories without the extra noise.
Testing conversational AI means moving beyond exact outputs, since valid responses vary. Instead, testers define quality criteria—accuracy, relevance, and clarity—while probing...
Compensator is a zero-config Laravel package implementing the Saga pattern for synchronous, multi-step rollbacks without queues or migrations.
Five criteria separate real AI code review tools from marketing noise — and most vendor benchmarks are measuring the wrong thing entirely.
Meta's Pocket app lets anyone build playable mini-games and gizmos in plain language, with results ready in under a minute.
Move your coding agent sessions between Claude Code, Codex, Cursor, and more — 64 routes, native resume, source never modified.
A structured roadmap for experienced developers to move beyond language familiarity and genuinely master the four core programming paradigms.