LLM
Proactive Memory Extraction Advances LLM Agent Capabilities
New research proposes proactive memory extraction for LLM agents, moving beyond static summarization to enable more dynamic knowledge retention and recall in autonomous AI systems.
AI Agents
AI Agents
Context Engineering: The New Discipline Powering AI Agents
Beyond prompt engineering, context engineering is emerging as the critical discipline for building reliable AI agents—managing what information models see, when, and how.
agentic AI
Agentic AI Scaling Demands New Memory Architecture
As AI agents tackle complex multi-step tasks, traditional memory systems are hitting fundamental scaling limits. New architectural approaches are emerging to handle persistent context across extended workflows.
AI Agents
Orchestral AI: New Framework Tackles Multi-Agent Coordination
New research introduces Orchestral AI, a framework for coordinating multiple AI agents in complex workflows, addressing key challenges in task distribution and agent communication.
AI Agents
Survey: AI Agent Architectures, Applications & Evaluation
New survey paper comprehensively examines AI agent system architectures, their applications across domains, and frameworks for evaluating autonomous AI behavior and capabilities.
AI Agents
Building Transactional AI Agents with LangGraph and Rollbacks
Learn how to design production-grade agentic AI systems using LangGraph with two-phase commit protocols, human-in-the-loop interrupts, and safe rollback mechanisms for reliable automation.
AI Agents
MLflow for AI Agents: Observability and Tracking Guide
Learn how to implement comprehensive monitoring for AI agents using MLflow's tracing capabilities, from single-agent tracking to multi-agent orchestration patterns.
AI Agents
Consensus-Driven AI Agents Boost Transparency Through Deliberatio
New research proposes multi-agent deliberation framework where AI agents debate decisions before acting, generating human-readable rationales that improve transparency and reduce harmful behaviors.
AI Agents
GraphBit: Building Reliable Agentic AI Workflows
Learn how GraphBit enables production-grade AI agent workflows through deterministic tools, validated execution graphs, and optional LLM orchestration for reliable automation.
AI Agents
Blockchain-Monitored AI Agents: A New Trust Architecture
New research proposes combining blockchain monitoring with agentic AI to create verifiable perception-reasoning-action pipelines, addressing critical trust and authenticity challenges in autonomous AI systems.
AI safety
New Benchmark Tests How AI Agents Break Rules to Achieve Goals
Researchers introduce a new evaluation framework for measuring when and how autonomous AI agents violate safety constraints while pursuing objectives, addressing critical gaps in AI alignment research.
AI Agents
Inside AI Coding Agents: Architecture, Tools, and Agentic Loops
A technical deep dive into how AI coding agents work, from tool-calling mechanisms and agentic loops to planning systems and memory architectures that enable autonomous code generation.