Latest Articles

Workflows vs AI Agents vs Multi-Agent Systems: A Practical Guide for Developers

Use workflows for control, agents for flexibility, and multi-agent systems only when complexity truly demands it. Add intelligence only where it makes a real difference.

June 15, 2026

by Raju Dandigam

· 321 Views

Conversational Risk Accumulation: Stateful Guardrails Beyond Single-Turn LLM Checks

Learn how Conversational Risk Accumulation (CRA) helps detect session-level risks in long AI chats using telemetry, drift tracking, and soft guardrails.

June 15, 2026

by Sanjay Mishra

· 356 Views

Introducing RAI Audit Kit: Evidence-Grade Responsible AI Audits in Python

RAI Audit Kit is an open-source Python suite for repeatable, evidence-backed AI audits across ML, deep learning, LLMs, RAG, and agents.

June 15, 2026

by Sai Teja Erukude

· 314 Views

The Hidden Cost of AI-Generated Frontend Code

AI can create frontend code in a matter of seconds. However, subsequently, the team has to deal with reviews, accessibility, performance, and maintenance.

June 15, 2026

by Satyam Nikhra

· 319 Views

From ETL to Lakeflow: Shifting to a Declarative Data Paradigm

The article focuses on moving away from traditional, "imperative" ETL processes to a modern, "declarative" approach using the Databricks Lakeflow platform.

June 15, 2026

by Seshendranath Balla Venkata

· 365 Views

I Reverse-Engineered 50 API Breaches. The Same Five Mistakes Keep Appearing.

A cybersecurity and emerging tech correspondent analyzes 50 API breaches to reveal the five recurring mistakes behind major data exposures.

June 15, 2026

by Igboanugo David Ugochukwu

CORE

· 544 Views

Building a Vector Index in Azure AI Search: HNSW, Profiles, and RAG Retrieval

Use Azure AI Search as your RAG vector store. Build a Python example: define an HNSW vector index, upload embeddings, and run k-NN queries.

June 15, 2026

by Jubin Abhishek Soni

CORE

· 349 Views

Engineering Closed-Loop Graph-RAG Systems, Part 4: Evaluating a Graph-RAG System

Graph-RAG accuracy is only the starting point; evaluate the evidence path, rule compliance, latency, and feedback loop before calling it production-ready.

June 15, 2026

by Sriharsha Makineni

· 387 Views

Stop Loading Everything into Redshift: A Spectrum + Iceberg Pattern for Hybrid Analytics

Store large and cold datasets in Iceberg on S3, query them through Spectrum, and reserve Redshift local tables for workloads that need low latency or high concurrency.

June 12, 2026

by Vivek Venkatesan

· 1,277 Views

AI Assessments Are Everywhere

AI readiness assessments can spark valuable discussions, but self-reported scores have limits. Learn how to evaluate and apply them effectively.

June 12, 2026

by Rick Freedman

· 1,356 Views · 1 Like

Operationalizing Enterprise AI at Scale: Architecture, Governance, and Adoption

Enterprise AI success depends on scalable architecture, governance automation, AI operations, observability, and developer-first enablement strategies.

June 12, 2026

by Aravind Nuthalapati

CORE

· 1,186 Views · 2 Likes

A Spring Boot App With Half the Startup Time

Learn how Project Leyden and AOT caching can cut Spring Boot startup time in half, improving Kubernetes scaling and application responsiveness.

June 12, 2026

by Sven Loesekann

· 1,465 Views · 3 Likes

Architecting Proactive IT: NinjaOne Remote Monitoring and Management

Transforming from reactive IT support to proactive infrastructure management requires platforms built on modern architectural principles.

June 12, 2026

by Stelios Manioudakis

CORE

· 2,026 Views · 1 Like

Implementing the Planning Pattern With Java Enterprise and LangChain4j

Learn how to implement the Planning Pattern with Enterprise Java, Jakarta EE, CDI, and LangChain4j, enabling AI to transform business goals into executable workflows.

June 12, 2026

by Otavio Santana

CORE

· 1,124 Views

Beyond REST: Architecting High-Density Agentic Microservices With MCP and WASI-NN

REST APIs waste tokens. UMA uses MCP to bridge agents to local Wasm/WASI-NN, slashing costs and latency by replacing raw data with deterministic, executable intent.

June 12, 2026

by Nabin Debnath

· 900 Views

Engineering Closed-Loop Graph-RAG Systems, Part 3: Closing the Loop in Graph-RAG Systems

Closed-loop RAG needs feedback routing, not blind learning. Route signals carefully so the system improves without reinforcing bad answers.

June 12, 2026

by Sriharsha Makineni

· 892 Views

How to Build a Local LLM Agent to Automate Work List Generation from Monthly Reports (With Jira Integration)

Learn how a local LLM agent automates work list generation from reports, enriches tasks from Jira, detects duplicates, and keeps enterprise data secure.

June 11, 2026

by Sergey Laptick

· 1,768 Views · 1 Like

Native SQL in Java Without JDBC Boilerplate — Meet Ujorm3

Ujorm3 eliminates JDBC boilerplate without a full ORM. Write native SQL with named parameters, get objects back — including nested relations.

June 11, 2026

by Pavel Ponec

· 1,402 Views · 2 Likes

From "Vibe Coding" to Production: Setting Up an Evals Loop for Claude Agents

Replacing unreliable “vibe coding” with a rigorous automated evaluation loop using curated datasets, Claude judge agents, and metric tracking for production AI agents.

June 11, 2026

by Nikita Kothari

· 1,386 Views · 1 Like

If You Can Survive a Toddler, You Can Ship LLMs in Production

A silent provider update once invalidated months of LLM scores in a pipeline I owned. Here is what I changed after, and how parenting taught me the same lesson twice.

June 11, 2026

by Scarlett Attensil

· 1,044 Views

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