Mapping the Unknown: Turning AI Safety from Space into Proof
A practical reading of how ODD coverage can turn safety-critical AI assurance from broad regulatory language into an auditable engineering process.
Cognaptus Insights
Industry thoughts, trends, and commentary.
The Art of Forgetting: Why Smarter AI Agents Need Selective Amnesia
A mechanism-first reading of adaptive budgeted forgetting for AI agents, and why enterprise memory systems should be governed like scarce capital rather than treated as infinite storage.
The Mood Doesn’t Move the Model — But It Can Route It
Emotional prompting rarely acts as a universal accuracy booster, but the paper shows why affective tone may still work as a weak input-dependent routing signal.
The Self-Driving Portfolio: When Your CIO Becomes an API
A mechanism-first reading of agentic strategic asset allocation: what becomes programmable, what remains governance, and why the paper is not a simple performance claim.
The Token Trial: Putting Words on the Stand in LLMs
A mechanism-first reading of VISTA, a lightweight token-attribution method that helps teams audit prompt semantics without mistaking embedding disruption for true LLM reasoning.
When AI Answers the Wrong Question — And Why That Matters More Than Being Wrong
A mechanism-first reading of Trace Inversion, a new abstention method that treats hallucination as query misalignment rather than mere answer error.
When AI Grades Itself: The Quiet Failure of LLM-as-a-Judge in Clinical Translation
A comparative reading of why fluent LLM-generated clinical translations can look excellent to AI judges while remaining misaligned with radiologist judgment.
When Language Models Ask for Help: The Curious Case of Uncertain AI
A comparison-based reading of ASK, an uncertainty-gated RL-LM architecture that shows why language models are useful in agentic systems only when routed carefully.
Agents That Remember: Why HERA Turns RAG into a System, Not a Trick
A mechanism-first reading of HERA, a training-free multi-agent RAG framework that turns past execution experience into orchestration policy, prompt evolution, and practical lessons for enterprise AI systems.
Autonomous Memory: When AI Starts Debugging Itself
A closer look at how Omni-SimpleMem shows that autonomous research pipelines can improve agent memory by finding the boring system failures humans usually miss.