Breaking the Question Apart: How Compositional Retrieval Reshapes RAG Performance
A practical reading of compositional retrieval: why RAG systems fail when evidence parts compete, and what coordinated retrieval changes for enterprise workflows.
Cognaptus Insights
Industry thoughts, trends, and commentary.
Cite Before You Write: Agentic RAG That Picks Graph vs. Vector on the Fly
A mechanism-first look at why dynamic retrieval routing, not generic summarisation, is the real advance in agentic literature-review RAG.
Fair or Foul? How LLMs ‘Appraise’ Emotions
A new appraisal benchmark shows why emotionally fluent LLMs can still reason about human emotions in fragile, uneven, and poorly localised ways.
From Ballots to Budgets: Can LLMs Be Trusted as Social Planners?
A mechanism-first reading of how participatory budgeting turns LLM resource allocation into a test of preference inference, constraint discipline, and operational trust.
From Byline to Botline: How LLMs Are Quietly Rewriting the News
A practical reading of new evidence on AI-generated news: where it is rising, how it changes writing, and why media governance now needs measurement rather than vibes.
Search When It Hurts: How UR² Teaches Models to Retrieve Only When Needed
UR² shows that better RAG is not about retrieving more, but about training smaller models to search selectively, compress evidence, and preserve reasoning.
EMAzing Trends: When One Moving Average Beats a Basket of Signals
A mechanism-first reading of why a single normalized EMA, tested through Agnostic Risk Parity, can challenge the usual trend-following habit of stacking many indicators.
Market’s Inner Circle: Finding Balance in Stock Networks
A statistically validated network method turns noisy stock correlations into interpretable risk clusters—and shows why China’s market core is more concentration warning than hedging map.
Taming the Trading Floor: How 'Roaree' Optimizers Could Redefine AI Stock Forecasting
A practical reading of Roaree’s MambaStock benchmark: optimiser choice changes speed, stability, and error, but not yet a trading strategy.
The Silent Skill Drain: How Entry-Level AI Automation Threatens Future Growth
AI automation can raise output today while weakening the apprentice-like pathways that create tomorrow’s experts.