Counterfactuals Unchained: How Causality Escapes Its Own Models
A formal causality paper shows why the real business question is not merely what caused an outcome, but which counterfactual language your explanation system is allowed to use.
Cognaptus Insights
Industry thoughts, trends, and commentary.
Cutting Through the Noise: How Programmatic Pruning Turns Web Agents into Real Operators
A mechanism-first analysis of Prune4Web and why reliable web agents may depend less on larger context windows than on better ways to shrink the page before reasoning begins.
Debate Club for Robots: How Multi-Agent Arguing Makes Embodied AI Safer
A mechanism-first reading of MADRA, a training-free multi-agent debate system that treats embodied AI safety as a decision-gate problem rather than a stronger-prompt problem.
Mind the Markov Gap: How a Lightweight Agent Outsmarts Heavy LLMs in Open-Vocabulary Vision
OVOD-Agent shows how a small Markov-Bandit reasoning layer can improve rare-category detection without putting an LLM in the detection loop.
Storm-Chasing Agents: How EWE Turns Extreme Weather into Actionable Intelligence
EWE shows how agentic AI can turn extreme-weather diagnosis from a scarce expert workflow into a structured, auditable climate-intelligence pipeline.
Watch This Space: How Two Simple Heuristics Outsmarted a Whole SAT Solver
A mechanism-first look at how coefficient-aware propagation heuristics improved RoundingSAT on large pseudo-Boolean benchmarks, and what that means for business optimization systems.
Error Hunting Season: Why Pessimism Makes LLMs Smarter at Math
A mechanism-first reading of pessimistic verification: why proof checking improves when models stop voting and start hunting for disqualifying errors.
Futures, Not Forecasts: How AI Redraws the Boundaries of Foresight
A sharp reading of responsible computational foresight: why AI’s strategic value lies less in predicting one future than in helping organizations rehearse many.
Loops, Latents, and the Unavoidable A Priori: Why Causal Modeling Needs Couple’s Therapy
A comparison-based reading of how system dynamics and structural equation modeling can share a mathematical language without pretending they solve the same causal problem.
Memory, But Make It Multimodal: How ViLoMem Rewires Agentic Learning
ViLoMem shows why multimodal AI agents need separate memories for visual traps and logical mistakes, and what that means for enterprise AI systems that must learn from repeated failures.