Carlos Daniel Jiménez · AI Software Engineer
Music, meaning,
and reliable AI.
I study how AI systems interpret and remember, through musical narratives and experiments you can examine.
An album can return to an idea without repeating its words. An agent can cite a source without supporting its answer. My work explores those gaps through music research and AI engineering.
A question to start with
Can a smaller context make an agent more expensive?
A four-album experiment follows the evidence and the model calls behind an answer. It asks what a memory policy saves, what it misses, and whether the evaluator can tell.
AI Software Engineering
Narrative Arcs in Music
For teams building with AI
Does the evidence support the answer?
I help teams examine retrieval, agent memory, and evaluation through a focused diagnostic: a bounded set of cases, a clear rubric, and recommendations grounded in the observed failures.
Explore a diagnostic →