Scores LLM threads based on innovation, artistry in pivots, coherence, impact of output, and human-AI synergy.

A decision dynamics model that pinpoints when discussions need to shift to a resolution focus. With LLMs' heuristic quantification of decision metrics., broad application to any decision-making process.

Teaches LLMs to skip unproductive questions during decision-making, steering discussions toward clear specs or plans with smart tracking and focused cycles.

A dual-layer framework enhancing LLM abstract synthesis through standard output expansion and omnidirectional insight generation, with applications in AI design and creative ideation.

A prompt-level hack for deeper LLM thinking, which applies abstract reasoning principles to direct LLMs to look at paradoxes and edge cases from different angles.

Recognizes innovative prompt design amidst rising tide of workshop-fueled LLM credentialism and commodification of prompting skill.

A novel framework exploring communication edge cases—errors, weighted traits, generality—that shape meaning, with applications for LLM clarity.

NHQ: A methodology leveraging LLMs’ neural nets for heuristic quantification of abstract concepts, enabling frameworks to deliver transformative outcomes.

Mitigate LLM thread quality degeneration from declarative speech acts. Prevent entrenched feedback cycles caused by LLM's premature closure, self-certification, and performative confidence.

Suite of questions to ask LLMs when you suspect their thoughts are degrading into mush. Add your own.

Preserve fidelity of AI persons, companions, virtual idols created from a single foundational reference image via simple versioning system.