Breaking Rules, Not Systems: How Penalties Make Autonomous Agents Behave
A case-first reading of how penalty-aware policy reasoning lets autonomous agents distinguish acceptable emergency exceptions from dangerous rule-breaking.
Cognaptus Insights
Industry thoughts, trends, and commentary.
Heuristics, Meet Your Agents: How Role-Based LLMs Rewire Optimization
RoCo shows how role-specialized LLM agents can improve automatic heuristic design—but its business value lies in disciplined solver augmentation, not magic optimization.
Memory, Multiplied: Why LLM Agents Need More Than Bigger Brains
MemVerse shows why persistent AI agents need structured multimodal memory, fast distilled recall, and evidence-grounded retrieval—not just longer context windows.
Rule of Thumb, Meet Rule of Code: How DeepRule Rewrites Retail Optimization
DeepRule shows how LLMs can turn messy retail knowledge into auditable assortment and pricing rules, but the real lesson is the pipeline, not the model.
Stacking the Odds: Why Blocksworld Still Breaks Your Fancy LLM Agent
A practical reading of an MCP-integrated Blocksworld benchmark showing why planning, verification, execution, and replanning must be tested together before LLM agents touch real operations.
Think Fast, Think Slow: How Omni-AutoThink Rewrites Multimodal Reasoning
A mechanism-first reading of Omni-AutoThink, showing why adaptive multimodal reasoning is a training problem, not a prompting trick.
When Research Becomes a Tree: Why Static-DRA Matters in an Agentic World
A mechanism-first analysis of Static-DRA, a tree-based deep research agent that turns research depth and breadth into explicit business controls.
Agents Without Prompts: When LLMs Finally Learn to Check Their Own Homework
A mechanism-first look at how prompt-free verification-refinement agents turn existing system prompts into reusable quality-control infrastructure for paper-to-code automation.
Counterfactuals, Concepts, and Causality: XAI Finally Gets Its Act Together
A causal concept-based XAI framework shows why useful model explanations need more than heatmaps, concept labels, and wishful thinking.
Digging Deeper with Bayes: Why AI May Finally Fix Mineral Exploration
A decision-science reading of why AI’s real value in mineral exploration may be reducing false-positive drilling, not replacing geologists.