..... ...... ..... ...... ..... ...... .. .. . .. .. .. .. .. .. .. .. .. .. .. .. ++ ++.... ++... ++.... ++... ++.... ++ ++ + . ++ ++ ++ + ++ ++ + ++ ++ ++ ++++ ** ** ** ** * ** ** * ** ** ** ** * ##### ###### ## # ###### ###### ###### ###### ###### ## #
this is how coding with AI should feel
LLMs cannot know the unspoken goals, constraints, and preferences specific to your projects.
LLMs accumulate clutter and a tangle of assumptions in your codebase after unexamined vibe-coding.
LLMs tend to be overconfident, insufficiently doubtful of their own actions and the text in front of them.
LLMs cannot foresee the full consequences over time of their edits into your codebase.
Cerebella is a runtime engine that notices when LLM interventions deviate from your goals.
Cerebella ensures LLMs are properly scrutinized, which LLMs really suck at doing themselves.
Cerebella's project-specific workflows run on-device, since local compute is often idle and unutilized.
Cerebella's runtime loop uses fast and reliable statistics, not LLMs, to steer LLMs away from avoidable errors.