Train of Thought: How Long-Haul RL Unlocks LLM Reasoning Diversity
A mechanism-first reading of NVIDIA’s prolonged reinforcement-learning recipe for making small reasoning models improve without collapsing into narrow, brittle behaviour.
Cognaptus Insights
Industry thoughts, trends, and commentary.
Beyond Search: RAG’s Awakening to Enterprise Spreadsheets
A mechanism-first look at why enterprise RAG needs row-aware tables, hybrid retrieval, reranking, and feedback loops before it can safely answer internal business questions.
Pricing Plans, Meet Prompt Engineering: LLMs and the Future of SaaS Monetization
A mechanism-first look at how LLMs can turn messy SaaS pricing pages into machine-readable pricing artifacts, and why the hard part is not scraping but disciplined pricing operations.
Truth, Beauty, Justice, and the Data Scientist’s Dilemma
A practical reading of why AI agents can automate much of analytics execution without replacing the human judgment that makes data science useful.
Beyond Stack Overflow: CodeAssistBench Exposes the Real Gaps in LLM Coding Help
CodeAssistBench shows why coding assistants that shine on Q&A benchmarks still struggle inside real, recent, multi-turn software support workflows.
Game of Prompts: How Game Theory and Agentic LLMs Are Rewriting Cybersecurity
A practical reading of how game theory and agentic LLMs can reshape cybersecurity architecture, from strategic threat modeling to multi-agent SOC workflows.
Homo Silicus Goes to Wall Street
A comparison-based reading of how leading LLMs answer financial preference questions, and why their synthetic rationality creates a suitability problem for AI finance.
Inside Out: How LLMs Are Learning to Feel (and Misfeel) Like Us
A logits-based method for mapping emotion hierarchies in LLMs turns affective AI evaluation from a label-accuracy contest into a structural audit problem.
Thoughts, Exposed: Why Chain-of-Thought Monitoring Might Be AI Safety’s Best Fragile Hope
A mechanism-first reading of why visible reasoning traces may offer a rare but fragile safety signal for agentic AI oversight.
Causality Pays: A Smarter Take on Volatility-Based Trading
A mechanism-first reading of Vol-TS, a volatility-and-causal-inference trading framework that turns noisy stock movement into directional lead-lag signals.