Cognaptus Insights

A mechanism-first reading of how one reusable visual perturbation can steer closed-source multimodal models toward a chosen target across unseen images.

A mechanism-first reading of why reliable AI agents need subsystem architecture, reusable design patterns, and clearer diagnosis than another enthusiastic list of agent tricks.

A new A* heuristic-design paper shows why algorithmic context can matter more than vague domain prompting when LLMs are used inside constrained optimization workflows.

A mechanism-first reading of why enterprise database routing fails when it relies on embeddings or prompt-only LLM reranking, and why schema coverage plus connectivity checks matter.

A mechanism-first reading of GAVEL, a rule-based activation monitoring framework that turns model-internal signals into auditable AI governance logic.

A mechanism-first reading of an AI molecular-glue pipeline for targeting amyloid-β42, and why its business value is disciplined triage rather than instant drug discovery.

Health-SCORE shows how reusable, adaptive rubrics can turn expert medical judgment into a scalable control layer for healthcare LLMs.

A mechanism-first reading of CASTER, a context-aware router that cuts multi-agent LLM costs by deciding when expensive reasoning is actually needed.

A mechanism-first reading of why visual generation helps reasoning only when the task needs a visual world model, not whenever a model can draw.

A practical reading of memorization-heavy evaluation: why models that remember too well can still be risky, and why controllable forgetting may need to be designed into training itself.