The Latest and Popular SDLC Topics

Going All In On the JVM 25 Virtual Threads

Learn how JDK 25 virtual threads let Spring applications replace reactive APIs with blocking code for simpler development, debugging, and efficient scaling.

October 14, 2026

by Sven Loesekann

· 2,005 Views · 1 Like

A Brown-Bag Project: babbler

babbler is a tiny, MIT-licensed brown-bag project that turns any counter number into a guaranteed-unique, pronounceable two-word name.

October 14, 2026

by Peter Verhas

CORE

· 996 Views

AI-Era Cybersecurity, Part 1: Mapping Glasswing, Daybreak, Lightwell and the Tools Racing to Find and Fix Bugs

AI is now used on both sides of the vulnerability fight: it finds bugs faster for defenders and shortens the time attackers need to weaponize them.

October 14, 2026

by Vidyasagar (Sarath Chandra) Machupalli FBCS

CORE

· 1,325 Views · 2 Likes

"Works on My Machine" Is an Architecture Problem

"Works on my machine" exposes architectural gaps in reproducibility, dependency control, runtime consistency, and environment-aware system design.

October 13, 2026

by Uthej Mopathi

CORE

· 1,371 Views · 1 Like

The LLM Evaluation Score Improved. Production Quality Didn't.

Higher LLM evaluation scores can hide production regressions when benchmarks, judges, datasets, and metrics miss real-world system behavior.

October 13, 2026

by Uthej Mopathi

CORE

· 1,349 Views · 1 Like

Builder Pattern + Faker in API Test Automation Using Playwright With TypeScript

Learn how to use the Builder Pattern with the Faker library in API Test automation with Playwright and TypeScript to generate dynamic test data.

October 13, 2026

by Faisal Khatri

CORE

· 1,468 Views

Who Should Grade Your AI? Rules vs LLM Judges vs Humans

Learn when to use rule-based graders, LLM-as-a-judge, or human review to build more accurate, scalable, and reliable AI evaluation systems.

October 13, 2026

by Yakaiah Bommishetti

· 1,119 Views · 1 Like

Building a Scope-Constrained AI Agent for Automated CI Failure Repair

Build a scope-constrained AI agent that diagnoses CI failures, limits code changes, generates minimal patches, and validates repairs through targeted tests and CI gates.

October 12, 2026

by Uthej Mopathi

CORE

· 1,282 Views · 1 Like

The Jobs Matrix for AI: Four Boxes Instead of 40 Tools

Learn how a 2×2 AI matrix helps Agile teams classify AI use cases as chatbots or agents based on authority, scope, ownership, and review needs.

October 12, 2026

by Stefan Wolpers

CORE

· 1,311 Views

Columnar Formats for AI Telemetry: Parquet vs Vortex With DuckDB

This article compares Parquet and Vortex with DuckDB for AI inference telemetry, showing how file format and row ordering affect query speed and storage.

October 12, 2026

by Bhala Ranganathan

CORE

· 1,829 Views

Running TypeSafe AI's Jev Inside Neo4j for Confidence-Aware Sentiment Decisions

Call TypeSafe AI's Jev from inside a Java UDF, returning a typed sentiment decision with explicit uncertainty information directly from Cypher.

October 12, 2026

by Akmal Chaudhri

CORE

· 1,605 Views

The Code Generation Bottleneck Is Gone. The Maintenance Bottleneck Isn't.

AI removes code-generation bottlenecks, but maintainability, ownership, review, and governance become software engineering’s new constraints.

October 12, 2026

by Uthej Mopathi

CORE

· 1,193 Views · 3 Likes

Production RAG and LLM Systems: A Simple Q&A Guide

Building a small RAG demo is easy. Making it work at production scale — millions of documents, real users, tight latency — is a different job entirely.

October 12, 2026

by Ram Ghadiyaram

CORE

· 1,089 Views

Why Standardized Connectivity Is Only Half the Enterprise AI Equation

Model Context Protocol can eliminate substantial integration friction, but production AI agents still need governance, tool discipline, and orchestration.

October 9, 2026

by Grant Spradlin

· 1,315 Views · 1 Like

Does a Bigger Context Window Mean Better Memory: Understanding Context Windows, Model Memory, and RAG

Context is temporary, model memory is learned, and RAG retrieves external knowledge. A larger context window means more input, not perfect recall or permanent memory.

October 9, 2026

by Yakaiah Bommishetti

· 1,714 Views · 2 Likes

Member Spotlight: Raghava Dittakavi

DZone Core Member Raghava Dittakavi shares why great engineers question assumptions, understand the impact behind every change, and optimize AI to accelerate their work.

October 9, 2026

by Dominique Pugh

· 1,395 Views · 3 Likes

Threat Modeling Context-Aware AI: A STRIDE Walkthrough

How to secure enterprise AI pipelines: a hands-on walkthrough of six threat categories, one reference architecture, and a prioritized list of fixes.

October 9, 2026

by Sandeep Gadde

· 1,438 Views · 4 Likes

Why Your GPU Fleet Is Both Full and Idle: Building a Capacity Orchestration Layer

Managing GPU capacity manually produces fleets that are simultaneously fully allocated and poorly utilized. A capacity orchestration layer can fix the problem.

October 9, 2026

by Ankit Sinha

· 1,375 Views · 1 Like

Production-Grade LLM Regression Testing: Contracts, Evals, and Quality Gates

AI regression testing combines deterministic contracts, behavioral evaluations, production failures, and baseline comparisons to prevent silent LLM regressions.

October 9, 2026

by Uthej Mopathi

CORE

· 1,240 Views · 1 Like

AI Governance Belongs in Your Pipeline, Not in Spreadsheets

Shift AI governance from spreadsheets to code by embedding automated Risk Appetite Statements into CI/CD pipelines as Architectural Fitness Functions.

October 8, 2026

by vikram isanaka

· 1,261 Views · 1 Like

The Latest Popular Topics