Applied AI Research
Every edition breaks down a peer-reviewed paper into actionable strategy. No hype — just evidence from the world's leading labs.
Previous Editions
The Answer Lives in the Graph
An LLM given nine typed graph primitives as tools outperforms hand-coded query handlers, proving the barrier is operator vocabulary not model intelligence.
Siemens Digital Industries Software
How Two Blocked Attacks Became One That Wasn't
Hybrid jailbreak methods combining token and prompt attacks bypass defenses on Vicuna-7B with 37-58% success rates where single attacks failed completely.
Purdue University
What If Querying 16 Million Records Cost the Same as 50
RES architecture cuts AI agent token costs to constant 1,574 tokens regardless of dataset size by processing data through deterministic code instead of LLM context windows.
Walmart Tech
What Happens When You Stop Building Around the LLM
A blueprint architecture orchestrates enterprise AI agents through streams and registries, enabling multi-modal data access and cost-optimized compound AI workflows.
Megagon Labs
SkillOpt: a Mechanism That Makes Skills Training Stable
SkillOpt optimizes agent skill documents like neural weights with validation gates and edit budgets, improving task accuracy by up to 39 points without model retraining.
Microsoft, Shanghai Jiao Tong University, Tongji University, Fudan University
92% Correct. Without Handing It the Answers.
AgenticRAG enables AI models to autonomously navigate enterprise documents through iterative tool use, improving retrieval accuracy 5.9× over single-shot methods while reducing token costs.
Microsoft
Safe Alone, Dangerous Together: The AI Agent Blind Spot
A governance taxonomy organizes AI agent interventions into five categories—alignment, control, visibility, security, and societal integration—to manage risks as agents approach human-level task performance.
IAPS (Institute for AI Policy and Strategy)
Every AI Agent Audit Your Teams Run Is Missing the Same Thing
ARC Framework governs agentic AI through a capability lens that maps 46 risks to 88 technical controls using structured implementation guidance.
GovTech Singapore, Singapore University of Technology and Design
The Attack Your Voice Agent Cannot Be Trained Out Of
The first red-teaming framework designed not for AI models in isolation, but for voice agents as they are actually deployed
Fordham University, IBM Research
The README That Makes AI Coding Agents 29% Faster
Adding AGENTS.md files to repositories reduces AI coding agent runtime by 29% and output tokens by 17% without changing task completion rates.
Singapore Management University, Heidelberg University, University of Bamberg, King's College London
The Guardrail Blocking Half Your AI Agent's Legitimate Work
AGrail uses two collaborative LLMs with adaptive memory to defend AI agents against attacks, blocking 96% of threats while preserving 96% of legitimate actions.
The Ohio State University, University of Wisconsin-Madison, University of California, Davis
The AI Agent That Learns From Its Own Work
SAGE, a reinforcement learning framework from AWS and UW-Madison, trains AI agents to write and reuse programmatic skills across chains of related tasks, achieving 8.9% higher scenario completion than RL-without-skills baselines while using 59% fewer tokens.
University of Wisconsin–Madison; AWS Agentic AI (Amazon)
77% Win Rate. This Is the RAG Architecture Behind It.
Atlassian's ADORE framework replaces single-pass RAG pipelines with a multi-agent, evidence-audited research loop that achieves a 77% win rate against ChatGPT Deep Research on business consulting tasks and outperforms all competitors on the DeepResearch Bench.
Atlassian
Your Workflow Automation Was Never Designed to Think
Researchers propose a five-layer architectural framework for Agentic BPM Systems (A-BPMS) that combines process mining, AI reasoning, and autonomous orchestration to move enterprise workflows beyond fixed rules into fully self-managing, self-optimizing operations.
University of Tartu
Agent Skills Don't Compound. The Framework That Changes That.
AgentSkillOS shows that structured skill composition via tree-based retrieval and DAG orchestration dramatically outperforms flat skill provisioning, even when agents have access to identical tools.
Shanghai Artificial Intelligence Laboratory
Your AI Vendor Has a Governance Problem
A Carnegie Mellon study reveals that Anthropic's Claude fails key transparency, bias, and accountability benchmarks under the NIST AI Risk Management Framework and EU AI Act, exposing significant governance gaps that enterprise buyers must audit before deployment.
Carnegie Mellon University, School of Computer Science, Privacy Engineering