InfoQ

QCon London 2026: Reliable Retrieval for Production AI Systems

At QCon London 2026, Lan Chu, AI Tech Lead at Rabobank, shared lessons from deploying a production AI search system used ...

Microsoft Confirms SQL Zero-Day Security Vulnerability—Here’s The Fix

Microsoft has confirmed that a hacker who successfully exploits a zero-day SQL vulnerability could gain system administrator privileges. Here’s how to fix it.
InfoQ

From Minutes to Seconds: Uber Boosts MySQL Cluster Uptime with Consensus Architecture

Uber redesigned its MySQL fleet using a consensus-driven architecture based on MySQL Group Replication, reducing cluster ...
ITWeb on MSN

SQL Server 2025: Redefining the modern data platform

SQL Server 2025: Redefining the modern data platformIssued by Ascent TechnologyJohannesburg, 11 Mar 2026 SQL Server 2025: Redefining the modern data platform. Explore how SQL Server 2025 reshapes the ...
WinBuzzer

New Databricks KARL RAG Agent Promises 33% Cost Reduction vs. Claude Opus 4.6

Databricks has released KARL, an RL-trained RAG agent that it says handles all six enterprise search categories at 33% lower ...

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 ...
IEEE

Advancing NLIDB Systems with T5-RAG: An Encoder-Decoder Approach to SQL Query Generation

Abstract: Interacting with relational databases often requires expertise in Structured Query Language (SQL), which limits accessibility for non-technical users. Natural Language Interfaces to ...
GitHub

RickyT715/Generative-AI-Multi-Agent-RAG-System

An intelligent multi-agent customer support system powered by LangGraph, featuring natural language querying of customer data (Text-to-SQL), company policy documents (RAG), and a conversational ...
IEEE

A Hybrid SQL-RAG-LLM Question Answering System for Plastic Waste Management

Abstract: Plastic waste management is a critical global challenge, demanding rapid synthesis of large and heterogeneous research outputs. Conventional literature review methods are labour-intensive, ...
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 ...
GitHub

agentic-dev-io/agent-farm

agent-farm/ ├── src/agent_farm/ # Main Python package │ ├── main.py # Entry point, MCP server initialization │ ├── spec_engine.py # Spec Engine class (central component) │ ├── orgs.py # Organization ...
VentureBeat

Most RAG systems don’t understand sophisticated documents — they shred them

But for industries dependent on heavy engineering, the reality has been underwhelming. Engineers ask specific questions about infrastructure, and the bot hallucinates. The failure isn't in the LLM.