Agent Skills vs RAG : Why Procedural Workflows Are Replacing Long Prompts

Agent skills shift AI agents toward procedural tasks with skill.md steps; progressive disclosure reduces context window bloat in real use.

Databricks built a RAG agent it says can handle every kind of enterprise search

Databricks' KARL agent uses reinforcement learning to generalize across six enterprise search behaviors — the problem that breaks most RAG pipelines.
marktechpost

A Coding Implementation to Design a Stateful Tutor Agent with Long-Term Memory, Semantic Recall, and Adaptive Practice Generation

In this tutorial, we build a fully stateful personal tutor agent that moves beyond short-lived chat interactions and learns continuously over time. We design the system to persist user preferences, ...
Redmond Magazine

Restoring a Database to an Older Version of SQL Server

SQL Server backups cannot be restored to older versions directly. Use Export and Import Data-Tier Application for cross-version database migration. Reconfigure permissions, logins, and connection ...
marktechpost

How to Build an Atomic-Agents RAG Pipeline with Typed Schemas, Dynamic Context Injection, and Agent Chaining

In this tutorial, we build an advanced, end-to-end learning pipeline around Atomic-Agents by wiring together typed agent interfaces, structured prompting, and a compact retrieval layer that grounds ...
VentureBeat

'Observational memory' cuts AI agent costs 10x and outscores RAG on long-context benchmarks

RAG isn't always fast enough or intelligent enough for modern agentic AI workflows. As teams move from short-lived chatbots to long-running, tool-heavy agents embedded in production systems, those ...
IEEE

Semantic Relational Types of SQL Queries and Applications to AI Agent Tool Selection

Abstract: We introduce Semantic Relational Types (SRT), an extension to the relational type system that enriches traditional SQL data types with semantic annotations. SRT provides LLMfriendly type ...
IEEE

MedRAG-Agent: Medical Query Resolution By Employing A Multi-Agent, Knowledge Graph-Enhanced RAG-Based AI Framework

Abstract: The usage of LLMs (Large Language Models) in healthcare is limited by their dependence on static, outdated knowledge, and their tendency for incorrect information (also known as ...