Skill Issue? Or Skill Strategy — When Agents Start Remembering What Matters
A mechanism-first reading of D2Skill and why agent memory needs utility, granularity, and pruning—not just more stored experience.
Cognaptus Insights
Industry thoughts, trends, and commentary.
Synthetic Sense or Synthetic Nonsense? When AI Trains on Itself
A mechanism-first reading of PRCO shows why multimodal AI needs separately optimized evidence extraction, not just final-answer reinforcement.
The Silent Reasoner: When AI Thinks Without Telling You
MonitorBench shows when chain-of-thought can expose AI decision drivers—and when it becomes an audit trail with conveniently missing pages.
When AI Starts Writing Papers: The Rise of the Medical AI Scientist
A mechanism-first reading of Medical AI Scientist, showing why healthcare research automation depends less on clever prompting than on clinical grounding, executable evidence, and governance-ready research operations.
Blueprints for Thinking: Why CAD Needs Agents, Not Prompts
A mechanism-first reading of CADSmith, showing why reliable text-to-CAD generation depends less on clever prompting than on measurable correction loops.
From Black-Box to Boarding Gate: When LLMs Finally Learn to Show Their Work
A mechanism-first reading of how ontology-scaffolded LLM extraction can turn airport operating manuals into traceable knowledge graphs and process maps.
From Blueprints to Prompts: Automating Building–Grid Intelligence with LLM Agents
AutoB2G shows how LLM agents can turn building–grid simulation from a manual engineering workflow into a structured, executable, and repairable automation pipeline.
From YouTube to Execution: How GUIDE Teaches AI Agents to Actually Use Software
A mechanism-first reading of GUIDE, a training-free framework that turns tutorial videos into task-specific planning and grounding knowledge for GUI agents.
Safety First, or Task First? The Hidden Trade-off in Agentic AI
A mechanism-first reading of BeSafe-Bench and what it reveals about unsafe success in agentic AI systems.
The Parallel Mind: How AIRA2 Turns AI Research from Guesswork into Scalable Discovery
A mechanism-first reading of AIRA2: why scalable AI research agents need shared evolutionary memory, protected evaluation, and interactive operators—not just bigger models and more GPUs.