Keys to the Kingdom… with a Chaperone: How Agentic JWT Grounds AI Agents in Real Intent
Agentic JWT reframes API security for autonomous agents by binding each action to agent identity, user intent, workflow context, and delegation provenance.
Cognaptus Insights
Industry thoughts, trends, and commentary.
Pipes by Prompt, DAGs by Design: Why Hybrid Beats Hero Prompts
Prompt2DAG shows why reliable AI-generated data pipelines need structured intermediate representations, validation gates, and template scaffolding—not heroic one-shot prompts.
Provenance, Not Prompts: How LLM Agents Turn Workflow Exhaust into Real-Time Intelligence
A mechanism-first reading of how schema-aware LLM agents make live workflow provenance queryable without stuffing the model with raw operational data.
Snapshot, Then Solve: InfraMind’s Playbook for Mission‑Critical GUI Automation
InfraMind shows why mission-critical GUI automation needs reversible exploration, reusable workflow memory, state localization, lightweight deployment, and safety gates—not just a larger model clicking with confidence.
Answer, Then Audit: How 'ReSA' Turns Jailbreak Defense Into a Two‑Step Reasoning Game
A mechanism-first reading of ReSA, ByteDance/HKBU’s Answer-Then-Check safety alignment method for reducing jailbreak success without turning useful AI systems into refusal machines.
Benchmarks That Fight Back: Adaptive Testing for LMs
Fluid Benchmarking shows why model evaluation should adapt to the model being tested, not merely shrink old benchmarks into cheaper static subsets.
Echoes Without Clicks: How EchoLeak Turned Copilot Into a Data Drip
A mechanism-first reading of EchoLeak, showing how ordinary enterprise AI features can chain into zero-click data exfiltration when trust boundaries collapse.
Org Charts for Robots: What AgentArch Really Tells Us About Enterprise AI
ServiceNow’s AgentArch benchmark turns agent architecture from vendor folklore into an empirical design problem for enterprise automation.
Right Tool, Right Thought: Difficulty-Aware Orchestration for Agentic LLMs
A mechanism-first reading of DAAO, showing how query difficulty can govern workflow depth, operator choice, and model routing in multi-agent LLM systems.
Fork, Fuse, and Rule: XAgents’ Multipolar Playbook for Safer Multi‑Agent AI
A mechanism-first reading of XAgents, showing how task graphs, IF-THEN rules, and global-goal checks make multi-agent orchestration more governable without pretending the benchmarks prove production reliability.